mirror of
https://github.com/osm-search/Nominatim.git
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763 lines
31 KiB
Python
763 lines
31 KiB
Python
# SPDX-License-Identifier: GPL-3.0-or-later
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#
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# This file is part of Nominatim. (https://nominatim.org)
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#
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# Copyright (C) 2025 by the Nominatim developer community.
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# For a full list of authors see the git log.
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"""
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Tokenizer implementing normalisation as used before Nominatim 4 but using
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libICU instead of the PostgreSQL module.
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"""
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from typing import Optional, Sequence, List, Tuple, Mapping, Any, cast, \
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Dict, Set, Iterable
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import itertools
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import logging
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from psycopg.types.json import Jsonb
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from psycopg import sql as pysql
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from ..db.connection import connect, Connection, Cursor, \
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drop_tables, table_exists, execute_scalar
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from ..config import Configuration
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from ..db.sql_preprocessor import SQLPreprocessor
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from ..data.place_info import PlaceInfo
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from ..data.place_name import PlaceName
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from .icu_rule_loader import ICURuleLoader
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from .place_sanitizer import PlaceSanitizer
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from .icu_token_analysis import ICUTokenAnalysis
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from .base import AbstractAnalyzer, AbstractTokenizer
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DBCFG_TERM_NORMALIZATION = "tokenizer_term_normalization"
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LOG = logging.getLogger()
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WORD_TYPES = (('country_names', 'C'),
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('postcodes', 'P'),
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('full_word', 'W'),
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('housenumbers', 'H'))
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def create(dsn: str) -> 'ICUTokenizer':
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""" Create a new instance of the tokenizer provided by this module.
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"""
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return ICUTokenizer(dsn)
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class ICUTokenizer(AbstractTokenizer):
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""" This tokenizer uses libICU to convert names and queries to ASCII.
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Otherwise it uses the same algorithms and data structures as the
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normalization routines in Nominatim 3.
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"""
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def __init__(self, dsn: str) -> None:
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self.dsn = dsn
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self.loader: Optional[ICURuleLoader] = None
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def init_new_db(self, config: Configuration, init_db: bool = True) -> None:
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""" Set up a new tokenizer for the database.
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This copies all necessary data in the project directory to make
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sure the tokenizer remains stable even over updates.
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"""
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self.loader = ICURuleLoader(config)
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self._save_config()
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if init_db:
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self.update_sql_functions(config)
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self._setup_db_tables(config)
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self._create_base_indices(config, 'word')
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def init_from_project(self, config: Configuration) -> None:
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""" Initialise the tokenizer from the project directory.
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"""
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self.loader = ICURuleLoader(config)
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with connect(self.dsn) as conn:
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self.loader.load_config_from_db(conn)
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def finalize_import(self, config: Configuration) -> None:
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""" Do any required postprocessing to make the tokenizer data ready
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for use.
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"""
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self._create_lookup_indices(config, 'word')
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def update_sql_functions(self, config: Configuration) -> None:
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""" Reimport the SQL functions for this tokenizer.
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"""
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with connect(self.dsn) as conn:
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sqlp = SQLPreprocessor(conn, config)
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sqlp.run_sql_file(conn, 'tokenizer/icu_tokenizer.sql')
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def check_database(self, config: Configuration) -> None:
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""" Check that the tokenizer is set up correctly.
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"""
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# Will throw an error if there is an issue.
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self.init_from_project(config)
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def update_statistics(self, config: Configuration, threads: int = 2) -> None:
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""" Recompute frequencies for all name words.
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"""
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with connect(self.dsn) as conn:
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if not table_exists(conn, 'search_name'):
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return
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with conn.cursor() as cur:
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cur.execute('ANALYSE search_name')
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if threads > 1:
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cur.execute(pysql.SQL('SET max_parallel_workers_per_gather TO {}')
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.format(pysql.Literal(min(threads, 6),)))
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LOG.info('Computing word frequencies')
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drop_tables(conn, 'word_frequencies')
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cur.execute("""
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CREATE TEMP TABLE word_frequencies AS
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WITH word_freq AS MATERIALIZED (
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SELECT unnest(name_vector) as id, count(*)
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FROM search_name GROUP BY id),
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addr_freq AS MATERIALIZED (
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SELECT unnest(nameaddress_vector) as id, count(*)
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FROM search_name GROUP BY id)
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SELECT coalesce(a.id, w.id) as id,
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(CASE WHEN w.count is null or w.count <= 1 THEN '{}'::JSONB
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ELSE jsonb_build_object('count', w.count) END
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||
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CASE WHEN a.count is null or a.count <= 1 THEN '{}'::JSONB
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ELSE jsonb_build_object('addr_count', a.count) END) as info
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FROM word_freq w FULL JOIN addr_freq a ON a.id = w.id;
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""")
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cur.execute('CREATE UNIQUE INDEX ON word_frequencies(id) INCLUDE(info)')
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cur.execute('ANALYSE word_frequencies')
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LOG.info('Update word table with recomputed frequencies')
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drop_tables(conn, 'tmp_word')
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cur.execute("""CREATE TABLE tmp_word AS
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SELECT word_id, word_token, type, word,
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coalesce(word.info, '{}'::jsonb)
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- 'count' - 'addr_count' ||
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coalesce(wf.info, '{}'::jsonb)
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as info
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FROM word LEFT JOIN word_frequencies wf
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ON word.word_id = wf.id
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""")
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drop_tables(conn, 'word_frequencies')
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with conn.cursor() as cur:
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cur.execute('SET max_parallel_workers_per_gather TO 0')
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sqlp = SQLPreprocessor(conn, config)
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sqlp.run_string(conn,
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'GRANT SELECT ON tmp_word TO "{{config.DATABASE_WEBUSER}}"')
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conn.commit()
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self._create_base_indices(config, 'tmp_word')
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self._create_lookup_indices(config, 'tmp_word')
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self._move_temporary_word_table('tmp_word')
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def _cleanup_housenumbers(self) -> None:
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""" Remove unused house numbers.
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"""
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with connect(self.dsn) as conn:
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if not table_exists(conn, 'search_name'):
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return
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with conn.cursor(name="hnr_counter") as cur:
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cur.execute("""SELECT DISTINCT word_id, coalesce(info->>'lookup', word_token)
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FROM word
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WHERE type = 'H'
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AND NOT EXISTS(SELECT * FROM search_name
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WHERE ARRAY[word.word_id] && name_vector)
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AND (char_length(coalesce(word, word_token)) > 6
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OR coalesce(word, word_token) not similar to '\\d+')
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""")
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candidates = {token: wid for wid, token in cur}
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with conn.cursor(name="hnr_counter") as cur:
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cur.execute("""SELECT housenumber FROM placex
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WHERE housenumber is not null
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AND (char_length(housenumber) > 6
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OR housenumber not similar to '\\d+')
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""")
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for row in cur:
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for hnr in row[0].split(';'):
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candidates.pop(hnr, None)
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LOG.info("There are %s outdated housenumbers.", len(candidates))
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LOG.debug("Outdated housenumbers: %s", candidates.keys())
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if candidates:
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with conn.cursor() as cur:
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cur.execute("""DELETE FROM word WHERE word_id = any(%s)""",
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(list(candidates.values()), ))
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conn.commit()
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def update_word_tokens(self) -> None:
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""" Remove unused tokens.
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"""
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LOG.warning("Cleaning up housenumber tokens.")
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self._cleanup_housenumbers()
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LOG.warning("Tokenizer house-keeping done.")
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def name_analyzer(self) -> 'ICUNameAnalyzer':
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""" Create a new analyzer for tokenizing names and queries
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using this tokinzer. Analyzers are context managers and should
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be used accordingly:
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```
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with tokenizer.name_analyzer() as analyzer:
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analyser.tokenize()
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```
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When used outside the with construct, the caller must ensure to
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call the close() function before destructing the analyzer.
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Analyzers are not thread-safe. You need to instantiate one per thread.
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"""
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assert self.loader is not None
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return ICUNameAnalyzer(self.dsn, self.loader.make_sanitizer(),
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self.loader.make_token_analysis())
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def most_frequent_words(self, conn: Connection, num: int) -> List[str]:
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""" Return a list of the `num` most frequent full words
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in the database.
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"""
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with conn.cursor() as cur:
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cur.execute("""SELECT word, sum((info->>'count')::int) as count
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FROM word WHERE type = 'W'
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GROUP BY word
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ORDER BY count DESC LIMIT %s""", (num,))
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return list(s[0].split('@')[0] for s in cur)
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def _save_config(self) -> None:
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""" Save the configuration that needs to remain stable for the given
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database as database properties.
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"""
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assert self.loader is not None
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with connect(self.dsn) as conn:
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self.loader.save_config_to_db(conn)
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def _setup_db_tables(self, config: Configuration) -> None:
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""" Set up the word table and fill it with pre-computed word
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frequencies.
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"""
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with connect(self.dsn) as conn:
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drop_tables(conn, 'word')
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sqlp = SQLPreprocessor(conn, config)
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sqlp.run_string(conn, """
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CREATE TABLE word (
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word_id INTEGER,
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word_token text NOT NULL,
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type text NOT NULL,
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word text,
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info jsonb
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) {{db.tablespace.search_data}};
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GRANT SELECT ON word TO "{{config.DATABASE_WEBUSER}}";
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DROP SEQUENCE IF EXISTS seq_word;
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CREATE SEQUENCE seq_word start 1;
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GRANT SELECT ON seq_word to "{{config.DATABASE_WEBUSER}}";
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""")
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conn.commit()
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def _create_base_indices(self, config: Configuration, table_name: str) -> None:
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""" Set up the word table and fill it with pre-computed word
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frequencies.
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"""
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with connect(self.dsn) as conn:
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sqlp = SQLPreprocessor(conn, config)
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sqlp.run_string(conn,
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"""CREATE INDEX idx_{{table_name}}_word_token ON {{table_name}}
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USING BTREE (word_token) {{db.tablespace.search_index}}""",
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table_name=table_name)
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for name, ctype in WORD_TYPES:
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sqlp.run_string(conn,
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"""CREATE INDEX idx_{{table_name}}_{{idx_name}} ON {{table_name}}
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USING BTREE (word) {{db.tablespace.address_index}}
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WHERE type = '{{column_type}}'
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""",
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table_name=table_name, idx_name=name,
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column_type=ctype)
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conn.commit()
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def _create_lookup_indices(self, config: Configuration, table_name: str) -> None:
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""" Create additional indexes used when running the API.
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"""
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with connect(self.dsn) as conn:
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sqlp = SQLPreprocessor(conn, config)
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# Index required for details lookup.
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sqlp.run_string(
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conn,
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"""
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CREATE INDEX IF NOT EXISTS idx_{{table_name}}_word_id
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ON {{table_name}} USING BTREE (word_id) {{db.tablespace.search_index}}
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""",
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table_name=table_name)
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conn.commit()
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def _move_temporary_word_table(self, old: str) -> None:
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""" Rename all tables and indexes used by the tokenizer.
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"""
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with connect(self.dsn) as conn:
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drop_tables(conn, 'word')
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with conn.cursor() as cur:
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cur.execute(f"ALTER TABLE {old} RENAME TO word")
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for idx in ('word_token', 'word_id'):
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cur.execute(f"""ALTER INDEX idx_{old}_{idx}
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RENAME TO idx_word_{idx}""")
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for name, _ in WORD_TYPES:
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cur.execute(f"""ALTER INDEX idx_{old}_{name}
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RENAME TO idx_word_{name}""")
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conn.commit()
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class ICUNameAnalyzer(AbstractAnalyzer):
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""" The ICU analyzer uses the ICU library for splitting names.
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Each instance opens a connection to the database to request the
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normalization.
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"""
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def __init__(self, dsn: str, sanitizer: PlaceSanitizer,
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token_analysis: ICUTokenAnalysis) -> None:
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self.conn: Optional[Connection] = connect(dsn)
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self.conn.autocommit = True
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self.sanitizer = sanitizer
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self.token_analysis = token_analysis
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self._cache = _TokenCache()
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def close(self) -> None:
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""" Free all resources used by the analyzer.
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"""
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if self.conn:
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self.conn.close()
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self.conn = None
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def _search_normalized(self, name: str) -> str:
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""" Return the search token transliteration of the given name.
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"""
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return cast(str, self.token_analysis.search.transliterate(name)).strip()
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def _normalized(self, name: str) -> str:
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""" Return the normalized version of the given name with all
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non-relevant information removed.
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"""
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return cast(str, self.token_analysis.normalizer.transliterate(name)).strip()
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def get_word_token_info(self, words: Sequence[str]) -> List[Tuple[str, str, Optional[int]]]:
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""" Return token information for the given list of words.
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If a word starts with # it is assumed to be a full name
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otherwise is a partial name.
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The function returns a list of tuples with
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(original word, word token, word id).
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The function is used for testing and debugging only
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and not necessarily efficient.
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"""
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assert self.conn is not None
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full_tokens = {}
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partial_tokens = {}
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for word in words:
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if word.startswith('#'):
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full_tokens[word] = self._search_normalized(word[1:])
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else:
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partial_tokens[word] = self._search_normalized(word)
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with self.conn.cursor() as cur:
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cur.execute("""SELECT word_token, word_id
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FROM word WHERE word_token = ANY(%s) and type = 'W'
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""", (list(full_tokens.values()),))
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full_ids = {r[0]: cast(int, r[1]) for r in cur}
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cur.execute("""SELECT word_token, word_id
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FROM word WHERE word_token = ANY(%s) and type = 'w'""",
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(list(partial_tokens.values()),))
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part_ids = {r[0]: cast(int, r[1]) for r in cur}
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return [(k, v, full_ids.get(v, None)) for k, v in full_tokens.items()] \
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+ [(k, v, part_ids.get(v, None)) for k, v in partial_tokens.items()]
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def normalize_postcode(self, postcode: str) -> str:
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""" Convert the postcode to a standardized form.
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This function must yield exactly the same result as the SQL function
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'token_normalized_postcode()'.
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"""
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return postcode.strip().upper()
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def update_postcodes_from_db(self) -> None:
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""" Postcode update.
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Removes all postcodes from the word table because they are not
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needed. Postcodes are recognised by pattern.
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"""
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assert self.conn is not None
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with self.conn.cursor() as cur:
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cur.execute("DELETE FROM word WHERE type = 'P'")
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def update_special_phrases(self, phrases: Iterable[Tuple[str, str, str, str]],
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should_replace: bool) -> None:
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""" Replace the search index for special phrases with the new phrases.
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If `should_replace` is True, then the previous set of will be
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completely replaced. Otherwise the phrases are added to the
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already existing ones.
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"""
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assert self.conn is not None
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norm_phrases = set(((self._normalized(p[0]), p[1], p[2], p[3])
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for p in phrases))
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with self.conn.cursor() as cur:
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# Get the old phrases.
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existing_phrases = set()
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cur.execute("SELECT word, info FROM word WHERE type = 'S'")
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for word, info in cur:
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existing_phrases.add((word, info['class'], info['type'],
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info.get('op') or '-'))
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added = self._add_special_phrases(cur, norm_phrases, existing_phrases)
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if should_replace:
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deleted = self._remove_special_phrases(cur, norm_phrases,
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existing_phrases)
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else:
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deleted = 0
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LOG.info("Total phrases: %s. Added: %s. Deleted: %s",
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len(norm_phrases), added, deleted)
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def _add_special_phrases(self, cursor: Cursor,
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new_phrases: Set[Tuple[str, str, str, str]],
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existing_phrases: Set[Tuple[str, str, str, str]]) -> int:
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""" Add all phrases to the database that are not yet there.
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"""
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to_add = new_phrases - existing_phrases
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added = 0
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with cursor.copy('COPY word(word_token, type, word, info) FROM STDIN') as copy:
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for word, cls, typ, oper in to_add:
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term = self._search_normalized(word)
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if term:
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copy.write_row((term, 'S', word,
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Jsonb({'class': cls, 'type': typ,
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'op': oper if oper in ('in', 'near') else None})))
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added += 1
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return added
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def _remove_special_phrases(self, cursor: Cursor,
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new_phrases: Set[Tuple[str, str, str, str]],
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existing_phrases: Set[Tuple[str, str, str, str]]) -> int:
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""" Remove all phrases from the database that are no longer in the
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new phrase list.
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"""
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to_delete = existing_phrases - new_phrases
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if to_delete:
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cursor.executemany(
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""" DELETE FROM word
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WHERE type = 'S' and word = %s
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and info->>'class' = %s and info->>'type' = %s
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and %s = coalesce(info->>'op', '-')
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""", to_delete)
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return len(to_delete)
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def add_country_names(self, country_code: str, names: Mapping[str, str]) -> None:
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""" Add default names for the given country to the search index.
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"""
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# Make sure any name preprocessing for country names applies.
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info = PlaceInfo({'name': names, 'country_code': country_code,
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'rank_address': 4, 'class': 'boundary',
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'type': 'administrative'})
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self._add_country_full_names(country_code,
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self.sanitizer.process_names(info)[0],
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internal=True)
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def _add_country_full_names(self, country_code: str, names: Sequence[PlaceName],
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internal: bool = False) -> None:
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""" Add names for the given country from an already sanitized
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name list.
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"""
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assert self.conn is not None
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word_tokens = set()
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for name in names:
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norm_name = self._search_normalized(name.name)
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if norm_name:
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word_tokens.add(norm_name)
|
|
|
|
with self.conn.cursor() as cur:
|
|
# Get existing names
|
|
cur.execute("""SELECT word_token, coalesce(info ? 'internal', false) as is_internal
|
|
FROM word
|
|
WHERE type = 'C' and word = %s""",
|
|
(country_code, ))
|
|
# internal/external names
|
|
existing_tokens: Dict[bool, Set[str]] = {True: set(), False: set()}
|
|
for word in cur:
|
|
existing_tokens[word[1]].add(word[0])
|
|
|
|
# Delete names that no longer exist.
|
|
gone_tokens = existing_tokens[internal] - word_tokens
|
|
if internal:
|
|
gone_tokens.update(existing_tokens[False] & word_tokens)
|
|
if gone_tokens:
|
|
cur.execute("""DELETE FROM word
|
|
USING unnest(%s::text[]) as token
|
|
WHERE type = 'C' and word = %s
|
|
and word_token = token""",
|
|
(list(gone_tokens), country_code))
|
|
|
|
# Only add those names that are not yet in the list.
|
|
new_tokens = word_tokens - existing_tokens[True]
|
|
if not internal:
|
|
new_tokens -= existing_tokens[False]
|
|
if new_tokens:
|
|
if internal:
|
|
sql = """INSERT INTO word (word_token, type, word, info)
|
|
(SELECT token, 'C', %s, '{"internal": "yes"}'
|
|
FROM unnest(%s::text[]) as token)
|
|
"""
|
|
else:
|
|
sql = """INSERT INTO word (word_token, type, word)
|
|
(SELECT token, 'C', %s
|
|
FROM unnest(%s::text[]) as token)
|
|
"""
|
|
cur.execute(sql, (country_code, list(new_tokens)))
|
|
|
|
def process_place(self, place: PlaceInfo) -> Mapping[str, Any]:
|
|
""" Determine tokenizer information about the given place.
|
|
|
|
Returns a JSON-serializable structure that will be handed into
|
|
the database via the token_info field.
|
|
"""
|
|
token_info = _TokenInfo()
|
|
|
|
names, address = self.sanitizer.process_names(place)
|
|
|
|
if names:
|
|
token_info.set_names(*self._compute_name_tokens(names))
|
|
|
|
if place.is_country():
|
|
assert place.country_code is not None
|
|
self._add_country_full_names(place.country_code, names)
|
|
|
|
if address:
|
|
self._process_place_address(token_info, address)
|
|
|
|
return token_info.to_dict()
|
|
|
|
def _process_place_address(self, token_info: '_TokenInfo',
|
|
address: Sequence[PlaceName]) -> None:
|
|
for item in address:
|
|
if item.kind == 'postcode':
|
|
token_info.set_postcode(self._add_postcode(item))
|
|
elif item.kind == 'housenumber':
|
|
token_info.add_housenumber(*self._compute_housenumber_token(item))
|
|
elif item.kind == 'street':
|
|
token_info.add_street(self._retrieve_full_tokens(item.name))
|
|
elif item.kind == 'place':
|
|
if not item.suffix:
|
|
token_info.add_place(itertools.chain(*self._compute_name_tokens([item])))
|
|
elif (not item.kind.startswith('_') and not item.suffix and
|
|
item.kind not in ('country', 'full', 'inclusion')):
|
|
token_info.add_address_term(item.kind,
|
|
itertools.chain(*self._compute_name_tokens([item])))
|
|
|
|
def _compute_housenumber_token(self, hnr: PlaceName) -> Tuple[Optional[int], Optional[str]]:
|
|
""" Normalize the housenumber and return the word token and the
|
|
canonical form.
|
|
"""
|
|
assert self.conn is not None
|
|
analyzer = self.token_analysis.analysis.get('@housenumber')
|
|
result: Tuple[Optional[int], Optional[str]] = (None, None)
|
|
|
|
if analyzer is None:
|
|
# When no custom analyzer is set, simply normalize and transliterate
|
|
norm_name = self._search_normalized(hnr.name)
|
|
if norm_name:
|
|
result = self._cache.housenumbers.get(norm_name, result)
|
|
if result[0] is None:
|
|
hid = execute_scalar(self.conn, "SELECT getorcreate_hnr_id(%s)", (norm_name, ))
|
|
|
|
result = hid, norm_name
|
|
self._cache.housenumbers[norm_name] = result
|
|
else:
|
|
# Otherwise use the analyzer to determine the canonical name.
|
|
# Per convention we use the first variant as the 'lookup name', the
|
|
# name that gets saved in the housenumber field of the place.
|
|
word_id = analyzer.get_canonical_id(hnr)
|
|
if word_id:
|
|
result = self._cache.housenumbers.get(word_id, result)
|
|
if result[0] is None:
|
|
varout = analyzer.compute_variants(word_id)
|
|
if isinstance(varout, tuple):
|
|
variants = varout[0]
|
|
else:
|
|
variants = varout
|
|
if variants:
|
|
hid = execute_scalar(self.conn, "SELECT create_analyzed_hnr_id(%s, %s)",
|
|
(word_id, variants))
|
|
result = hid, variants[0]
|
|
self._cache.housenumbers[word_id] = result
|
|
|
|
return result
|
|
|
|
def _retrieve_full_tokens(self, name: str) -> List[int]:
|
|
""" Get the full name token for the given name, if it exists.
|
|
The name is only retrieved for the standard analyser.
|
|
"""
|
|
assert self.conn is not None
|
|
norm_name = self._search_normalized(name)
|
|
|
|
# return cached if possible
|
|
if norm_name in self._cache.fulls:
|
|
return self._cache.fulls[norm_name]
|
|
|
|
with self.conn.cursor() as cur:
|
|
cur.execute("SELECT word_id FROM word WHERE word_token = %s and type = 'W'",
|
|
(norm_name, ))
|
|
full = [row[0] for row in cur]
|
|
|
|
self._cache.fulls[norm_name] = full
|
|
|
|
return full
|
|
|
|
def _compute_name_tokens(self, names: Sequence[PlaceName]) -> Tuple[Set[int], Set[int]]:
|
|
""" Computes the full name and partial name tokens for the given
|
|
dictionary of names.
|
|
"""
|
|
assert self.conn is not None
|
|
full_tokens: Set[int] = set()
|
|
partial_tokens: Set[int] = set()
|
|
|
|
for name in names:
|
|
analyzer_id = name.get_attr('analyzer')
|
|
analyzer = self.token_analysis.get_analyzer(analyzer_id)
|
|
word_id = analyzer.get_canonical_id(name)
|
|
if analyzer_id is None:
|
|
token_id = word_id
|
|
else:
|
|
token_id = f'{word_id}@{analyzer_id}'
|
|
|
|
full, part = self._cache.names.get(token_id, (None, None))
|
|
if full is None:
|
|
varset = analyzer.compute_variants(word_id)
|
|
if isinstance(varset, tuple):
|
|
variants, lookups = varset
|
|
else:
|
|
variants, lookups = varset, None
|
|
if not variants:
|
|
continue
|
|
|
|
with self.conn.cursor() as cur:
|
|
cur.execute("SELECT * FROM getorcreate_full_word(%s, %s, %s)",
|
|
(token_id, variants, lookups))
|
|
full, part = cast(Tuple[int, List[int]], cur.fetchone())
|
|
|
|
self._cache.names[token_id] = (full, part)
|
|
|
|
assert part is not None
|
|
|
|
full_tokens.add(full)
|
|
partial_tokens.update(part)
|
|
|
|
return full_tokens, partial_tokens
|
|
|
|
def _add_postcode(self, item: PlaceName) -> Optional[str]:
|
|
""" Make sure the normalized postcode is present in the word table.
|
|
"""
|
|
assert self.conn is not None
|
|
analyzer = self.token_analysis.analysis.get('@postcode')
|
|
|
|
if analyzer is None:
|
|
return item.name.strip().upper()
|
|
else:
|
|
return analyzer.get_canonical_id(item)
|
|
|
|
|
|
class _TokenInfo:
|
|
""" Collect token information to be sent back to the database.
|
|
"""
|
|
def __init__(self) -> None:
|
|
self.names: Optional[str] = None
|
|
self.housenumbers: Set[str] = set()
|
|
self.housenumber_tokens: Set[int] = set()
|
|
self.street_tokens: Optional[Set[int]] = None
|
|
self.place_tokens: Set[int] = set()
|
|
self.address_tokens: Dict[str, str] = {}
|
|
self.postcode: Optional[str] = None
|
|
|
|
def _mk_array(self, tokens: Iterable[Any]) -> str:
|
|
return f"{{{','.join((str(s) for s in tokens))}}}"
|
|
|
|
def to_dict(self) -> Dict[str, Any]:
|
|
""" Return the token information in database importable format.
|
|
"""
|
|
out: Dict[str, Any] = {}
|
|
|
|
if self.names:
|
|
out['names'] = self.names
|
|
|
|
if self.housenumbers:
|
|
out['hnr'] = ';'.join(self.housenumbers)
|
|
out['hnr_tokens'] = self._mk_array(self.housenumber_tokens)
|
|
|
|
if self.street_tokens is not None:
|
|
out['street'] = self._mk_array(self.street_tokens)
|
|
|
|
if self.place_tokens:
|
|
out['place'] = self._mk_array(self.place_tokens)
|
|
|
|
if self.address_tokens:
|
|
out['addr'] = self.address_tokens
|
|
|
|
if self.postcode:
|
|
out['postcode'] = self.postcode
|
|
|
|
return out
|
|
|
|
def set_names(self, fulls: Iterable[int], partials: Iterable[int]) -> None:
|
|
""" Adds token information for the normalised names.
|
|
"""
|
|
self.names = self._mk_array(itertools.chain(fulls, partials))
|
|
|
|
def add_housenumber(self, token: Optional[int], hnr: Optional[str]) -> None:
|
|
""" Extract housenumber information from a list of normalised
|
|
housenumbers.
|
|
"""
|
|
if token:
|
|
assert hnr is not None
|
|
self.housenumbers.add(hnr)
|
|
self.housenumber_tokens.add(token)
|
|
|
|
def add_street(self, tokens: Iterable[int]) -> None:
|
|
""" Add addr:street match terms.
|
|
"""
|
|
if self.street_tokens is None:
|
|
self.street_tokens = set()
|
|
self.street_tokens.update(tokens)
|
|
|
|
def add_place(self, tokens: Iterable[int]) -> None:
|
|
""" Add addr:place search and match terms.
|
|
"""
|
|
self.place_tokens.update(tokens)
|
|
|
|
def add_address_term(self, key: str, partials: Iterable[int]) -> None:
|
|
""" Add additional address terms.
|
|
"""
|
|
array = self._mk_array(partials)
|
|
if len(array) > 2:
|
|
self.address_tokens[key] = array
|
|
|
|
def set_postcode(self, postcode: Optional[str]) -> None:
|
|
""" Set the postcode to the given one.
|
|
"""
|
|
self.postcode = postcode
|
|
|
|
|
|
class _TokenCache:
|
|
""" Cache for token information to avoid repeated database queries.
|
|
|
|
This cache is not thread-safe and needs to be instantiated per
|
|
analyzer.
|
|
"""
|
|
def __init__(self) -> None:
|
|
self.names: Dict[str, Tuple[int, List[int]]] = {}
|
|
self.partials: Dict[str, int] = {}
|
|
self.fulls: Dict[str, List[int]] = {}
|
|
self.housenumbers: Dict[str, Tuple[Optional[int], Optional[str]]] = {}
|