adapt to new type annotations from typeshed

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

diff --git a/nominatim/tokenizer/legacy_tokenizer.py b/nominatim/tokenizer/legacy_tokenizer.py
index 6ffdc4ef46cc0269348428d8ba7abb76d872f3b0..1b0b2980f9048f0fb42ac82e9b5bc8c8fe4f6298 100644 (file)
--- a/nominatim/tokenizer/legacy_tokenizer.py
+++ b/nominatim/tokenizer/legacy_tokenizer.py
@@ -1,31 +1,46 @@
+# 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.
 """
 """
 Tokenizer implementing normalisation as used before Nominatim 4.
 """

+from typing import Optional, Sequence, List, Tuple, Mapping, Any, Callable, \
+                   cast, Dict, Set, Iterable
+from collections import OrderedDict

 import logging
 import logging

+from pathlib import Path

 import re
 import shutil
 import re
 import shutil

+from textwrap import dedent

 
 

+from icu import Transliterator

 import psycopg2
 import psycopg2.extras
 
 import psycopg2
 import psycopg2.extras
 

-from nominatim.db.connection import connect
+from nominatim.db.connection import connect, Connection
+from nominatim.config import Configuration

 from nominatim.db import properties
 from nominatim.db import utils as db_utils
 from nominatim.db.sql_preprocessor import SQLPreprocessor
 from nominatim.db import properties
 from nominatim.db import utils as db_utils
 from nominatim.db.sql_preprocessor import SQLPreprocessor

+from nominatim.data.place_info import PlaceInfo

 from nominatim.errors import UsageError
 from nominatim.errors import UsageError

+from nominatim.tokenizer.base import AbstractAnalyzer, AbstractTokenizer

 
 DBCFG_NORMALIZATION = "tokenizer_normalization"
 DBCFG_MAXWORDFREQ = "tokenizer_maxwordfreq"
 
 LOG = logging.getLogger()
 
 
 DBCFG_NORMALIZATION = "tokenizer_normalization"
 DBCFG_MAXWORDFREQ = "tokenizer_maxwordfreq"
 
 LOG = logging.getLogger()
 

-def create(dsn, data_dir):
+def create(dsn: str, data_dir: Path) -> 'LegacyTokenizer':

     """ Create a new instance of the tokenizer provided by this module.
     """
     return LegacyTokenizer(dsn, data_dir)
 
 
     """ Create a new instance of the tokenizer provided by this module.
     """
     return LegacyTokenizer(dsn, data_dir)
 
 

-def _install_module(config_module_path, src_dir, module_dir):
+def _install_module(config_module_path: str, src_dir: Path, module_dir: Path) -> str:

     """ Copies the PostgreSQL normalisation module into the project
         directory if necessary. For historical reasons the module is
         saved in the '/module' subdirectory and not with the other tokenizer
     """ Copies the PostgreSQL normalisation module into the project
         directory if necessary. For historical reasons the module is
         saved in the '/module' subdirectory and not with the other tokenizer


@@ -42,7 +57,7 @@ def _install_module(config_module_path, src_dir, module_dir):
     # Compatibility mode for builddir installations.
     if module_dir.exists() and src_dir.samefile(module_dir):
         LOG.info('Running from build directory. Leaving database module as is.')
     # Compatibility mode for builddir installations.
     if module_dir.exists() and src_dir.samefile(module_dir):
         LOG.info('Running from build directory. Leaving database module as is.')

-        return module_dir
+        return str(module_dir)

 
     # In any other case install the module in the project directory.
     if not module_dir.exists():
 
     # In any other case install the module in the project directory.
     if not module_dir.exists():


@@ -54,38 +69,38 @@ def _install_module(config_module_path, src_dir, module_dir):
 
     LOG.info('Database module installed at %s', str(destfile))
 
 
     LOG.info('Database module installed at %s', str(destfile))
 

-    return module_dir
+    return str(module_dir)

 
 
 
 

-def _check_module(module_dir, conn):
+def _check_module(module_dir: str, conn: Connection) -> None:

     """ Try to use the PostgreSQL module to confirm that it is correctly
         installed and accessible from PostgreSQL.
     """
     with conn.cursor() as cur:
         try:
             cur.execute("""CREATE FUNCTION nominatim_test_import_func(text)
     """ Try to use the PostgreSQL module to confirm that it is correctly
         installed and accessible from PostgreSQL.
     """
     with conn.cursor() as cur:
         try:
             cur.execute("""CREATE FUNCTION nominatim_test_import_func(text)

-                           RETURNS text AS '{}/nominatim.so', 'transliteration'
+                           RETURNS text AS %s, 'transliteration'

                            LANGUAGE c IMMUTABLE STRICT;
                            DROP FUNCTION nominatim_test_import_func(text)
                            LANGUAGE c IMMUTABLE STRICT;
                            DROP FUNCTION nominatim_test_import_func(text)

-                        """.format(module_dir))
+                        """, (f'{module_dir}/nominatim.so', ))

         except psycopg2.DatabaseError as err:
             LOG.fatal("Error accessing database module: %s", err)
             raise UsageError("Database module cannot be accessed.") from err
 
 
         except psycopg2.DatabaseError as err:
             LOG.fatal("Error accessing database module: %s", err)
             raise UsageError("Database module cannot be accessed.") from err
 
 

-class LegacyTokenizer:
+class LegacyTokenizer(AbstractTokenizer):

     """ The legacy tokenizer uses a special PostgreSQL module to normalize
         names and queries. The tokenizer thus implements normalization through
         calls to the database.
     """
 
     """ The legacy tokenizer uses a special PostgreSQL module to normalize
         names and queries. The tokenizer thus implements normalization through
         calls to the database.
     """
 

-    def __init__(self, dsn, data_dir):
+    def __init__(self, dsn: str, data_dir: Path) -> None:

         self.dsn = dsn
         self.data_dir = data_dir
         self.dsn = dsn
         self.data_dir = data_dir

-        self.normalization = None
+        self.normalization: Optional[str] = None

 
 
 
 

-    def init_new_db(self, config):
+    def init_new_db(self, config: Configuration, init_db: bool = True) -> None:

         """ Set up a new tokenizer for the database.
 
             This copies all necessary data in the project directory to make
         """ Set up a new tokenizer for the database.
 
             This copies all necessary data in the project directory to make


@@ -97,23 +112,41 @@ class LegacyTokenizer:
 
         self.normalization = config.TERM_NORMALIZATION
 
 
         self.normalization = config.TERM_NORMALIZATION
 

+        self._install_php(config, overwrite=True)
+

         with connect(self.dsn) as conn:
             _check_module(module_dir, conn)
             self._save_config(conn, config)
             conn.commit()
 
         with connect(self.dsn) as conn:
             _check_module(module_dir, conn)
             self._save_config(conn, config)
             conn.commit()
 

-        self.update_sql_functions(config)
-        self._init_db_tables(config)
+        if init_db:
+            self.update_sql_functions(config)
+            self._init_db_tables(config)

 
 
 
 

-    def init_from_project(self):
+    def init_from_project(self, config: Configuration) -> None:

         """ Initialise the tokenizer from the project directory.
         """
         with connect(self.dsn) as conn:
             self.normalization = properties.get_property(conn, DBCFG_NORMALIZATION)
 
         """ Initialise the tokenizer from the project directory.
         """
         with connect(self.dsn) as conn:
             self.normalization = properties.get_property(conn, DBCFG_NORMALIZATION)
 

+        if not (config.project_dir / 'module' / 'nominatim.so').exists():
+            _install_module(config.DATABASE_MODULE_PATH,
+                            config.lib_dir.module,
+                            config.project_dir / 'module')
+
+        self._install_php(config, overwrite=False)
+
+    def finalize_import(self, config: Configuration) -> None:
+        """ Do any required postprocessing to make the tokenizer data ready
+            for use.
+        """
+        with connect(self.dsn) as conn:
+            sqlp = SQLPreprocessor(conn, config)
+            sqlp.run_sql_file(conn, 'tokenizer/legacy_tokenizer_indices.sql')

 
 

-    def update_sql_functions(self, config):
+
+    def update_sql_functions(self, config: Configuration) -> None:

         """ Reimport the SQL functions for this tokenizer.
         """
         with connect(self.dsn) as conn:
         """ Reimport the SQL functions for this tokenizer.
         """
         with connect(self.dsn) as conn:


@@ -126,13 +159,41 @@ class LegacyTokenizer:
                               modulepath=modulepath)
 
 
                               modulepath=modulepath)
 
 

-    def migrate_database(self, config):
+    def check_database(self, _: Configuration) -> Optional[str]:
+        """ Check that the tokenizer is set up correctly.
+        """
+        hint = """\
+             The Postgresql extension nominatim.so was not correctly loaded.
+
+             Error: {error}
+
+             Hints:
+             * Check the output of the CMmake/make installation step
+             * Does nominatim.so exist?
+             * Does nominatim.so exist on the database server?
+             * Can nominatim.so be accessed by the database user?
+             """
+        with connect(self.dsn) as conn:
+            with conn.cursor() as cur:
+                try:
+                    out = cur.scalar("SELECT make_standard_name('a')")
+                except psycopg2.Error as err:
+                    return hint.format(error=str(err))
+
+        if out != 'a':
+            return hint.format(error='Unexpected result for make_standard_name()')
+
+        return None
+
+
+    def migrate_database(self, config: Configuration) -> None:

         """ Initialise the project directory of an existing database for
             use with this tokenizer.
 
             This is a special migration function for updating existing databases
             to new software versions.
         """
         """ Initialise the project directory of an existing database for
             use with this tokenizer.
 
             This is a special migration function for updating existing databases
             to new software versions.
         """

+        self.normalization = config.TERM_NORMALIZATION

         module_dir = _install_module(config.DATABASE_MODULE_PATH,
                                      config.lib_dir.module,
                                      config.project_dir / 'module')
         module_dir = _install_module(config.DATABASE_MODULE_PATH,
                                      config.lib_dir.module,
                                      config.project_dir / 'module')


@@ -142,7 +203,33 @@ class LegacyTokenizer:
             self._save_config(conn, config)
 
 
             self._save_config(conn, config)
 
 

-    def name_analyzer(self):
+    def update_statistics(self) -> None:
+        """ Recompute the frequency of full words.
+        """
+        with connect(self.dsn) as conn:
+            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) -> None:
+        """ No house-keeping implemented for the legacy tokenizer.
+        """
+        LOG.info("No tokenizer clean-up available.")
+
+
+    def name_analyzer(self) -> 'LegacyNameAnalyzer':

         """ Create a new analyzer for tokenizing names and queries
             using this tokinzer. Analyzers are context managers and should
             be used accordingly:
         """ Create a new analyzer for tokenizing names and queries
             using this tokinzer. Analyzers are context managers and should
             be used accordingly:


@@ -157,10 +244,26 @@ class LegacyTokenizer:
 
             Analyzers are not thread-safe. You need to instantiate one per thread.
         """
 
             Analyzers are not thread-safe. You need to instantiate one per thread.
         """

-        return LegacyNameAnalyzer(self.dsn)
+        normalizer = Transliterator.createFromRules("phrase normalizer",
+                                                    self.normalization)
+        return LegacyNameAnalyzer(self.dsn, normalizer)
+
+
+    def _install_php(self, config: Configuration, overwrite: bool = True) -> None:
+        """ Install the php script for the tokenizer.
+        """
+        php_file = self.data_dir / "tokenizer.php"
+
+        if not php_file.exists() or overwrite:
+            php_file.write_text(dedent(f"""\
+                <?php
+                @define('CONST_Max_Word_Frequency', {config.MAX_WORD_FREQUENCY});
+                @define('CONST_Term_Normalization_Rules', "{config.TERM_NORMALIZATION}");
+                require_once('{config.lib_dir.php}/tokenizer/legacy_tokenizer.php');
+                """), encoding='utf-8')

 
 
 
 

-    def _init_db_tables(self, config):
+    def _init_db_tables(self, config: Configuration) -> None:

         """ Set up the word table and fill it with pre-computed word
             frequencies.
         """
         """ Set up the word table and fill it with pre-computed word
             frequencies.
         """


@@ -173,16 +276,17 @@ class LegacyTokenizer:
         db_utils.execute_file(self.dsn, config.lib_dir.data / 'words.sql')
 
 
         db_utils.execute_file(self.dsn, config.lib_dir.data / 'words.sql')
 
 

-    def _save_config(self, conn, config):
+    def _save_config(self, conn: Connection, config: Configuration) -> None:

         """ Save the configuration that needs to remain stable for the given
             database as database properties.
         """
         """ Save the configuration that needs to remain stable for the given
             database as database properties.
         """

+        assert self.normalization is not None
+

         properties.set_property(conn, DBCFG_NORMALIZATION, self.normalization)
         properties.set_property(conn, DBCFG_MAXWORDFREQ, config.MAX_WORD_FREQUENCY)
 
 
         properties.set_property(conn, DBCFG_NORMALIZATION, self.normalization)
         properties.set_property(conn, DBCFG_MAXWORDFREQ, config.MAX_WORD_FREQUENCY)
 
 

-
-class LegacyNameAnalyzer:
+class LegacyNameAnalyzer(AbstractAnalyzer):

     """ The legacy analyzer uses the special Postgresql module for
         splitting names.
 
     """ The legacy analyzer uses the special Postgresql module for
         splitting names.
 


@@ -190,81 +294,239 @@ class LegacyNameAnalyzer:
         normalization.
     """
 
         normalization.
     """
 

-    def __init__(self, dsn):
-        self.conn = connect(dsn).connection
+    def __init__(self, dsn: str, normalizer: Any):
+        self.conn: Optional[Connection] = connect(dsn).connection

         self.conn.autocommit = True
         self.conn.autocommit = True

+        self.normalizer = normalizer

         psycopg2.extras.register_hstore(self.conn)
 
         self._cache = _TokenCache(self.conn)
 
 
         psycopg2.extras.register_hstore(self.conn)
 
         self._cache = _TokenCache(self.conn)
 
 

-    def __enter__(self):
-        return self
-
-
-    def __exit__(self, exc_type, exc_value, traceback):
-        self.close()
-
-
-    def close(self):
+    def close(self) -> None:

         """ Free all resources used by the analyzer.
         """
         if self.conn:
             self.conn.close()
             self.conn = None
 
         """ Free all resources used by the analyzer.
         """
         if self.conn:
             self.conn.close()
             self.conn = None
 

-    def process_place(self, place):
+
+    def get_word_token_info(self, words: Sequence[str]) -> List[Tuple[str, str, int]]:
+        """ Return token information for the given list of words.
+            If a word starts with # it is assumed to be a full name
+            otherwise is a partial name.
+
+            The function returns a list of tuples with
+            (original word, word token, word id).
+
+            The function is used for testing and debugging only
+            and not necessarily efficient.
+        """
+        assert self.conn is not None
+        with self.conn.cursor() as cur:
+            cur.execute("""SELECT t.term, word_token, word_id
+                           FROM word, (SELECT unnest(%s::TEXT[]) as term) t
+                           WHERE word_token = (CASE
+                                   WHEN left(t.term, 1) = '#' THEN
+                                     ' ' || make_standard_name(substring(t.term from 2))
+                                   ELSE
+                                     make_standard_name(t.term)
+                                   END)
+                                 and class is null and country_code is null""",
+                        (words, ))
+
+            return [(r[0], r[1], r[2]) for r in cur]
+
+
+    def normalize(self, phrase: str) -> str:
+        """ Normalize the given phrase, i.e. remove all properties that
+            are irrelevant for search.
+        """
+        return cast(str, self.normalizer.transliterate(phrase))
+
+
+    def normalize_postcode(self, postcode: str) -> str:
+        """ Convert the postcode to a standardized form.
+
+            This function must yield exactly the same result as the SQL function
+            'token_normalized_postcode()'.
+        """
+        return postcode.strip().upper()
+
+
+    def update_postcodes_from_db(self) -> None:
+        """ Update postcode tokens in the word table from the location_postcode
+            table.
+        """
+        assert self.conn is not None
+
+        with self.conn.cursor() as cur:
+            # This finds us the rows in location_postcode and word that are
+            # missing in the other table.
+            cur.execute("""SELECT * FROM
+                            (SELECT pc, word FROM
+                              (SELECT distinct(postcode) as pc FROM location_postcode) p
+                              FULL JOIN
+                              (SELECT word FROM word
+                                WHERE class ='place' and type = 'postcode') w
+                              ON pc = word) x
+                           WHERE pc is null or word is null""")
+
+            to_delete = []
+            to_add = []
+
+            for postcode, word in cur:
+                if postcode is None:
+                    to_delete.append(word)
+                else:
+                    to_add.append(postcode)
+
+            if to_delete:
+                cur.execute("""DELETE FROM WORD
+                               WHERE class ='place' and type = 'postcode'
+                                     and word = any(%s)
+                            """, (to_delete, ))
+            if to_add:
+                cur.execute("""SELECT count(create_postcode_id(pc))
+                               FROM unnest(%s) as pc
+                            """, (to_add, ))
+
+
+
+    def update_special_phrases(self, phrases: Iterable[Tuple[str, str, str, str]],
+                               should_replace: bool) -> None:
+        """ Replace the search index for special phrases with the new phrases.
+        """
+        assert self.conn is not None
+
+        norm_phrases = set(((self.normalize(p[0]), p[1], p[2], p[3])
+                            for p in phrases))
+
+        with self.conn.cursor() as cur:
+            # Get the old phrases.
+            existing_phrases = set()
+            cur.execute("""SELECT word, class, type, operator FROM word
+                           WHERE class != 'place'
+                                 OR (type != 'house' AND type != 'postcode')""")
+            for label, cls, typ, oper in cur:
+                existing_phrases.add((label, cls, typ, oper or '-'))
+
+            to_add = norm_phrases - existing_phrases
+            to_delete = existing_phrases - norm_phrases
+
+            if to_add:
+                cur.execute_values(
+                    """ INSERT INTO word (word_id, word_token, word, class, type,
+                                          search_name_count, operator)
+                        (SELECT nextval('seq_word'), ' ' || make_standard_name(name), name,
+                                class, type, 0,
+                                CASE WHEN op in ('in', 'near') THEN op ELSE null END
+                           FROM (VALUES %s) as v(name, class, type, op))""",
+                    to_add)
+
+            if to_delete and should_replace:
+                cur.execute_values(
+                    """ DELETE FROM word USING (VALUES %s) as v(name, in_class, in_type, op)
+                        WHERE word = name and class = in_class and type = in_type
+                              and ((op = '-' and operator is null) or op = operator)""",
+                    to_delete)
+
+        LOG.info("Total phrases: %s. Added: %s. Deleted: %s",
+                 len(norm_phrases), len(to_add), len(to_delete))
+
+
+    def add_country_names(self, country_code: str, names: Mapping[str, str]) -> None:
+        """ Add names for the given country to the search index.
+        """
+        assert self.conn is not None
+
+        with self.conn.cursor() as cur:
+            cur.execute(
+                """INSERT INTO word (word_id, word_token, country_code)
+                   (SELECT nextval('seq_word'), lookup_token, %s
+                      FROM (SELECT DISTINCT ' ' || make_standard_name(n) as lookup_token
+                            FROM unnest(%s)n) y
+                      WHERE NOT EXISTS(SELECT * FROM word
+                                       WHERE word_token = lookup_token and country_code = %s))
+                """, (country_code, list(names.values()), country_code))
+
+
+    def process_place(self, place: PlaceInfo) -> Mapping[str, Any]:

         """ Determine tokenizer information about the given place.
 
             Returns a JSON-serialisable structure that will be handed into
             the database via the token_info field.
         """
         """ Determine tokenizer information about the given place.
 
             Returns a JSON-serialisable structure that will be handed into
             the database via the token_info field.
         """

+        assert self.conn is not None
+

         token_info = _TokenInfo(self._cache)
 
         token_info = _TokenInfo(self._cache)
 

-        token_info.add_names(self.conn, place.get('name'), place.get('country_feature'))
+        names = place.name

 
 

-        address = place.get('address')
+        if names:
+            token_info.add_names(self.conn, names)

 
 

+            if place.is_country():
+                assert place.country_code is not None
+                self.add_country_names(place.country_code, names)
+
+        address = place.address

         if address:
         if address:

-            token_info.add_housenumbers(self.conn, address)
+            self._process_place_address(token_info, address)

 
         return token_info.data
 
 
 
         return token_info.data
 
 

+    def _process_place_address(self, token_info: '_TokenInfo', address: Mapping[str, str]) -> None:
+        assert self.conn is not None
+        hnrs = []
+        addr_terms = []
+
+        for key, value in address.items():
+            if key == 'postcode':
+                # Make sure the normalized postcode is present in the word table.
+                if re.search(r'[:,;]', value) is None:
+                    norm_pc = self.normalize_postcode(value)
+                    token_info.set_postcode(norm_pc)
+                    self._cache.add_postcode(self.conn, norm_pc)
+            elif key in ('housenumber', 'streetnumber', 'conscriptionnumber'):
+                hnrs.append(value)
+            elif key == 'street':
+                token_info.add_street(self.conn, value)
+            elif key == 'place':
+                token_info.add_place(self.conn, value)
+            elif not key.startswith('_') \
+                 and key not in ('country', 'full', 'inclusion'):
+                addr_terms.append((key, value))
+
+        if hnrs:
+            token_info.add_housenumbers(self.conn, hnrs)
+
+        if addr_terms:
+            token_info.add_address_terms(self.conn, addr_terms)
+
+
+

 class _TokenInfo:
     """ Collect token information to be sent back to the database.
     """
 class _TokenInfo:
     """ Collect token information to be sent back to the database.
     """

-    def __init__(self, cache):
+    def __init__(self, cache: '_TokenCache') -> None:

         self.cache = cache
         self.cache = cache

-        self.data = {}
+        self.data: Dict[str, Any] = {}

 
 
 
 

-    def add_names(self, conn, names, country_feature):
+    def add_names(self, conn: Connection, names: Mapping[str, str]) -> None:

         """ Add token information for the names of the place.
         """
         """ Add token information for the names of the place.
         """

-        if not names:
-            return
-

         with conn.cursor() as cur:
             # Create the token IDs for all names.
             self.data['names'] = cur.scalar("SELECT make_keywords(%s)::text",
                                             (names, ))
 
         with conn.cursor() as cur:
             # Create the token IDs for all names.
             self.data['names'] = cur.scalar("SELECT make_keywords(%s)::text",
                                             (names, ))
 

-            # Add country tokens to word table if necessary.
-            if country_feature and re.fullmatch(r'[A-Za-z][A-Za-z]', country_feature):
-                cur.execute("SELECT create_country(%s, %s)",
-                            (names, country_feature.lower()))

 
 

-
-    def add_housenumbers(self, conn, address):
+    def add_housenumbers(self, conn: Connection, hnrs: Sequence[str]) -> None:

         """ Extract housenumber information from the address.
         """
         """ Extract housenumber information from the address.
         """

-        hnrs = [v for k, v in address.items()
-                if k in ('housenumber', 'streetnumber', 'conscriptionnumber')]
-
-        if not hnrs:
-            return
-

         if len(hnrs) == 1:
             token = self.cache.get_housenumber(hnrs[0])
             if token is not None:
         if len(hnrs) == 1:
             token = self.cache.get_housenumber(hnrs[0])
             if token is not None:


@@ -273,7 +535,7 @@ class _TokenInfo:
                 return
 
         # split numbers if necessary
                 return
 
         # split numbers if necessary

-        simple_list = []
+        simple_list: List[str] = []

         for hnr in hnrs:
             simple_list.extend((x.strip() for x in re.split(r'[;,]', hnr)))
 
         for hnr in hnrs:
             simple_list.extend((x.strip() for x in re.split(r'[;,]', hnr)))
 


@@ -281,8 +543,89 @@ class _TokenInfo:
             simple_list = list(set(simple_list))
 
         with conn.cursor() as cur:
             simple_list = list(set(simple_list))
 
         with conn.cursor() as cur:

-            cur.execute("SELECT (create_housenumbers(%s)).* ", (simple_list, ))
-            self.data['hnr_tokens'], self.data['hnr'] = cur.fetchone()
+            cur.execute("SELECT * FROM create_housenumbers(%s)", (simple_list, ))
+            result = cur.fetchone()
+            assert result is not None
+            self.data['hnr_tokens'], self.data['hnr'] = result
+
+
+    def set_postcode(self, postcode: str) -> None:
+        """ Set or replace the postcode token with the given value.
+        """
+        self.data['postcode'] = postcode
+
+    def add_street(self, conn: Connection, street: str) -> None:
+        """ Add addr:street match terms.
+        """
+        def _get_street(name: str) -> List[int]:
+            with conn.cursor() as cur:
+                return cast(List[int],
+                            cur.scalar("SELECT word_ids_from_name(%s)::text", (name, )))
+
+        tokens = self.cache.streets.get(street, _get_street)
+        if tokens:
+            self.data['street'] = tokens
+
+
+    def add_place(self, conn: Connection, place: str) -> None:
+        """ Add addr:place search and match terms.
+        """
+        def _get_place(name: str) -> Tuple[List[int], List[int]]:
+            with conn.cursor() as cur:
+                cur.execute("""SELECT make_keywords(hstore('name' , %s))::text,
+                                      word_ids_from_name(%s)::text""",
+                            (name, name))
+                return cast(Tuple[List[int], List[int]], cur.fetchone())
+
+        self.data['place_search'], self.data['place_match'] = \
+            self.cache.places.get(place, _get_place)
+
+
+    def add_address_terms(self, conn: Connection, terms: Sequence[Tuple[str, str]]) -> None:
+        """ Add additional address terms.
+        """
+        def _get_address_term(name: str) -> Tuple[List[int], List[int]]:
+            with conn.cursor() as cur:
+                cur.execute("""SELECT addr_ids_from_name(%s)::text,
+                                      word_ids_from_name(%s)::text""",
+                            (name, name))
+                return cast(Tuple[List[int], List[int]], cur.fetchone())
+
+        tokens = {}
+        for key, value in terms:
+            items = self.cache.address_terms.get(value, _get_address_term)
+            if items[0] or items[1]:
+                tokens[key] = items
+
+        if tokens:
+            self.data['addr'] = tokens
+
+
+class _LRU:
+    """ Least recently used cache that accepts a generator function to
+        produce the item when there is a cache miss.
+    """
+
+    def __init__(self, maxsize: int = 128):
+        self.data: 'OrderedDict[str, Any]' = OrderedDict()
+        self.maxsize = maxsize
+
+
+    def get(self, key: str, generator: Callable[[str], Any]) -> Any:
+        """ Get the item with the given key from the cache. If nothing
+            is found in the cache, generate the value through the
+            generator function and store it in the cache.
+        """
+        value = self.data.get(key)
+        if value is not None:
+            self.data.move_to_end(key)
+        else:
+            value = generator(key)
+            if len(self.data) >= self.maxsize:
+                self.data.popitem(last=False)
+            self.data[key] = value
+
+        return value

 
 
 class _TokenCache:
 
 
 class _TokenCache:


@@ -291,15 +634,31 @@ class _TokenCache:
         This cache is not thread-safe and needs to be instantiated per
         analyzer.
     """
         This cache is not thread-safe and needs to be instantiated per
         analyzer.
     """

-    def __init__(self, conn):
+    def __init__(self, conn: Connection):
+        # various LRU caches
+        self.streets = _LRU(maxsize=256)
+        self.places = _LRU(maxsize=128)
+        self.address_terms = _LRU(maxsize=1024)
+

         # Lookup houseunumbers up to 100 and cache them
         with conn.cursor() as cur:
             cur.execute("""SELECT i, ARRAY[getorcreate_housenumber_id(i::text)]::text
                            FROM generate_series(1, 100) as i""")
         # Lookup houseunumbers up to 100 and cache them
         with conn.cursor() as cur:
             cur.execute("""SELECT i, ARRAY[getorcreate_housenumber_id(i::text)]::text
                            FROM generate_series(1, 100) as i""")

-            self._cached_housenumbers = {str(r[0]) : r[1] for r in cur}
+            self._cached_housenumbers: Dict[str, str] = {str(r[0]): r[1] for r in cur}

 
 

+        # For postcodes remember the ones that have already been added
+        self.postcodes: Set[str] = set()

 
 

-    def get_housenumber(self, number):
+    def get_housenumber(self, number: str) -> Optional[str]:

         """ Get a housenumber token from the cache.
         """
         return self._cached_housenumbers.get(number)
         """ Get a housenumber token from the cache.
         """
         return self._cached_housenumbers.get(number)

+
+
+    def add_postcode(self, conn: Connection, postcode: str) -> None:
+        """ Make sure the given postcode is in the database.
+        """
+        if postcode not in self.postcodes:
+            with conn.cursor() as cur:
+                cur.execute('SELECT create_postcode_id(%s)', (postcode, ))
+            self.postcodes.add(postcode)