mirror of
https://github.com/osm-search/Nominatim.git
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a0ed80d821
Automatically repopulate the tokenizer/ directory with the PHP stub and the postgresql module, when the directory is missing. This allows to switch working directories and in particular run the service from a different maschine then where it was installed. Users still need to make sure that .env files are set up correctly or they will shoot themselves in the foot. See #2515.
718 lines
26 KiB
Python
718 lines
26 KiB
Python
# SPDX-License-Identifier: GPL-2.0-only
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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) 2022 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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import itertools
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import json
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import logging
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import re
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from textwrap import dedent
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from nominatim.db.connection import connect
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from nominatim.db.utils import CopyBuffer
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from nominatim.db.sql_preprocessor import SQLPreprocessor
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from nominatim.indexer.place_info import PlaceInfo
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from nominatim.tokenizer.icu_rule_loader import ICURuleLoader
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from nominatim.tokenizer.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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def create(dsn, data_dir):
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""" Create a new instance of the tokenizer provided by this module.
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"""
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return LegacyICUTokenizer(dsn, data_dir)
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class LegacyICUTokenizer(AbstractTokenizer):
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""" This tokenizer uses libICU to covert 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, data_dir):
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self.dsn = dsn
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self.data_dir = data_dir
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self.loader = None
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def init_new_db(self, config, init_db=True):
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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._install_php(config.lib_dir.php, overwrite=True)
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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._init_db_tables(config)
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def init_from_project(self, config):
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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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self._install_php(config.lib_dir.php, overwrite=False)
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def finalize_import(self, config):
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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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with connect(self.dsn) as conn:
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sqlp = SQLPreprocessor(conn, config)
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sqlp.run_sql_file(conn, 'tokenizer/legacy_tokenizer_indices.sql')
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def update_sql_functions(self, config):
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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):
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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):
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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 conn.table_exists('search_name'):
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with conn.cursor() as cur:
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cur.drop_table("word_frequencies")
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LOG.info("Computing word frequencies")
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cur.execute("""CREATE TEMP TABLE word_frequencies AS
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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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cur.execute("CREATE INDEX ON word_frequencies(id)")
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LOG.info("Update word table with recomputed frequencies")
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cur.execute("""UPDATE word
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SET info = info || jsonb_build_object('count', count)
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FROM word_frequencies WHERE word_id = id""")
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cur.drop_table("word_frequencies")
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conn.commit()
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def _cleanup_housenumbers(self):
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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 conn.table_exists('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):
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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):
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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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return LegacyICUNameAnalyzer(self.dsn, self.loader.make_sanitizer(),
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self.loader.make_token_analysis())
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def _install_php(self, phpdir, overwrite=True):
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""" Install the php script for the tokenizer.
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"""
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php_file = self.data_dir / "tokenizer.php"
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if not php_file.exists() or overwrite:
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php_file.write_text(dedent(f"""\
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<?php
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@define('CONST_Max_Word_Frequency', 10000000);
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@define('CONST_Term_Normalization_Rules', "{self.loader.normalization_rules}");
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@define('CONST_Transliteration', "{self.loader.get_search_rules()}");
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require_once('{phpdir}/tokenizer/icu_tokenizer.php');"""))
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def _save_config(self):
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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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with connect(self.dsn) as conn:
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self.loader.save_config_to_db(conn)
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def _init_db_tables(self, config):
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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_sql_file(conn, 'tokenizer/icu_tokenizer_tables.sql')
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conn.commit()
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class LegacyICUNameAnalyzer(AbstractAnalyzer):
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""" The legacy 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, sanitizer, token_analysis):
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self.conn = connect(dsn).connection
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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):
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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):
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""" Return the search token transliteration of the given name.
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"""
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return self.token_analysis.search.transliterate(name).strip()
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def _normalized(self, name):
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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 self.token_analysis.normalizer.transliterate(name).strip()
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def get_word_token_info(self, words):
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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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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]: 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]: 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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@staticmethod
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def normalize_postcode(postcode):
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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):
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""" Update postcode tokens in the word table from the location_postcode
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table.
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"""
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to_delete = []
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with self.conn.cursor() as cur:
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# This finds us the rows in location_postcode and word that are
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# missing in the other table.
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cur.execute("""SELECT * FROM
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(SELECT pc, word FROM
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(SELECT distinct(postcode) as pc FROM location_postcode) p
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FULL JOIN
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(SELECT word FROM word WHERE type = 'P') w
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ON pc = word) x
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WHERE pc is null or word is null""")
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with CopyBuffer() as copystr:
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for postcode, word in cur:
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if postcode is None:
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to_delete.append(word)
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else:
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copystr.add(self._search_normalized(postcode),
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'P', postcode)
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if to_delete:
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cur.execute("""DELETE FROM WORD
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WHERE type ='P' and word = any(%s)
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""", (to_delete, ))
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copystr.copy_out(cur, 'word',
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columns=['word_token', 'type', 'word'])
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def update_special_phrases(self, phrases, should_replace):
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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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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, new_phrases, existing_phrases):
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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 CopyBuffer() as copystr:
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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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copystr.add(term, 'S', word,
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json.dumps({'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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copystr.copy_out(cursor, 'word',
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columns=['word_token', 'type', 'word', 'info'])
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return added
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@staticmethod
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def _remove_special_phrases(cursor, new_phrases, existing_phrases):
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""" Remove all phrases from the databse 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.execute_values(
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""" DELETE FROM word USING (VALUES %s) as v(name, in_class, in_type, op)
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WHERE type = 'S' and word = name
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and info->>'class' = in_class and info->>'type' = in_type
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and ((op = '-' and info->>'op' is null) or op = 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, names):
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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, names, internal=False):
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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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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)
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with self.conn.cursor() as cur:
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# Get existing names
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cur.execute("""SELECT word_token, coalesce(info ? 'internal', false) as is_internal
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FROM word
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WHERE type = 'C' and word = %s""",
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(country_code, ))
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existing_tokens = {True: set(), False: set()} # internal/external names
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for word in cur:
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existing_tokens[word[1]].add(word[0])
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# Delete names that no longer exist.
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gone_tokens = existing_tokens[internal] - word_tokens
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if internal:
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gone_tokens.update(existing_tokens[False] & word_tokens)
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if gone_tokens:
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cur.execute("""DELETE FROM word
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USING unnest(%s) as token
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WHERE type = 'C' and word = %s
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and word_token = token""",
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(list(gone_tokens), country_code))
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# Only add those names that are not yet in the list.
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new_tokens = word_tokens - existing_tokens[True]
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if not internal:
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new_tokens -= existing_tokens[False]
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if new_tokens:
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if internal:
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sql = """INSERT INTO word (word_token, type, word, info)
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(SELECT token, 'C', %s, '{"internal": "yes"}'
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FROM unnest(%s) as token)
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"""
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else:
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sql = """INSERT INTO word (word_token, type, word)
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(SELECT token, 'C', %s
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FROM unnest(%s) as token)
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"""
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cur.execute(sql, (country_code, list(new_tokens)))
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def process_place(self, place):
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""" Determine tokenizer information about the given place.
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Returns a JSON-serializable structure that will be handed into
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the database via the token_info field.
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"""
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token_info = _TokenInfo()
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names, address = self.sanitizer.process_names(place)
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if names:
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token_info.set_names(*self._compute_name_tokens(names))
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if place.is_country():
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self._add_country_full_names(place.country_code, names)
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if address:
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self._process_place_address(token_info, address)
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return token_info.to_dict()
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def _process_place_address(self, token_info, address):
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for item in address:
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if item.kind == 'postcode':
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self._add_postcode(item.name)
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elif item.kind == 'housenumber':
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token_info.add_housenumber(*self._compute_housenumber_token(item))
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elif item.kind == 'street':
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token_info.add_street(self._retrieve_full_tokens(item.name))
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elif item.kind == 'place':
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if not item.suffix:
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token_info.add_place(self._compute_partial_tokens(item.name))
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elif not item.kind.startswith('_') and not item.suffix and \
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item.kind not in ('country', 'full'):
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token_info.add_address_term(item.kind, self._compute_partial_tokens(item.name))
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def _compute_housenumber_token(self, hnr):
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""" Normalize the housenumber and return the word token and the
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canonical form.
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"""
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analyzer = self.token_analysis.analysis.get('@housenumber')
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result = None, None
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if analyzer is None:
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# When no custom analyzer is set, simply normalize and transliterate
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norm_name = self._search_normalized(hnr.name)
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if norm_name:
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result = self._cache.housenumbers.get(norm_name, result)
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if result[0] is None:
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with self.conn.cursor() as cur:
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cur.execute("SELECT getorcreate_hnr_id(%s)", (norm_name, ))
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result = cur.fetchone()[0], norm_name
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self._cache.housenumbers[norm_name] = result
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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.
|
|
norm_name = analyzer.normalize(hnr.name)
|
|
if norm_name:
|
|
result = self._cache.housenumbers.get(norm_name, result)
|
|
if result[0] is None:
|
|
variants = analyzer.get_variants_ascii(norm_name)
|
|
if variants:
|
|
with self.conn.cursor() as cur:
|
|
cur.execute("SELECT create_analyzed_hnr_id(%s, %s)",
|
|
(norm_name, list(variants)))
|
|
result = cur.fetchone()[0], variants[0]
|
|
self._cache.housenumbers[norm_name] = result
|
|
|
|
return result
|
|
|
|
|
|
def _compute_partial_tokens(self, name):
|
|
""" Normalize the given term, split it into partial words and return
|
|
then token list for them.
|
|
"""
|
|
norm_name = self._search_normalized(name)
|
|
|
|
tokens = []
|
|
need_lookup = []
|
|
for partial in norm_name.split():
|
|
token = self._cache.partials.get(partial)
|
|
if token:
|
|
tokens.append(token)
|
|
else:
|
|
need_lookup.append(partial)
|
|
|
|
if need_lookup:
|
|
with self.conn.cursor() as cur:
|
|
cur.execute("""SELECT word, getorcreate_partial_word(word)
|
|
FROM unnest(%s) word""",
|
|
(need_lookup, ))
|
|
|
|
for partial, token in cur:
|
|
tokens.append(token)
|
|
self._cache.partials[partial] = token
|
|
|
|
return tokens
|
|
|
|
|
|
def _retrieve_full_tokens(self, name):
|
|
""" Get the full name token for the given name, if it exists.
|
|
The name is only retrived for the standard analyser.
|
|
"""
|
|
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):
|
|
""" Computes the full name and partial name tokens for the given
|
|
dictionary of names.
|
|
"""
|
|
full_tokens = set()
|
|
partial_tokens = set()
|
|
|
|
for name in names:
|
|
analyzer_id = name.get_attr('analyzer')
|
|
analyzer = self.token_analysis.get_analyzer(analyzer_id)
|
|
norm_name = analyzer.normalize(name.name)
|
|
if analyzer_id is None:
|
|
token_id = norm_name
|
|
else:
|
|
token_id = f'{norm_name}@{analyzer_id}'
|
|
|
|
full, part = self._cache.names.get(token_id, (None, None))
|
|
if full is None:
|
|
variants = analyzer.get_variants_ascii(norm_name)
|
|
if not variants:
|
|
continue
|
|
|
|
with self.conn.cursor() as cur:
|
|
cur.execute("SELECT * FROM getorcreate_full_word(%s, %s)",
|
|
(token_id, variants))
|
|
full, part = cur.fetchone()
|
|
|
|
self._cache.names[token_id] = (full, part)
|
|
|
|
full_tokens.add(full)
|
|
partial_tokens.update(part)
|
|
|
|
return full_tokens, partial_tokens
|
|
|
|
|
|
def _add_postcode(self, postcode):
|
|
""" Make sure the normalized postcode is present in the word table.
|
|
"""
|
|
if re.search(r'[:,;]', postcode) is None:
|
|
postcode = self.normalize_postcode(postcode)
|
|
|
|
if postcode not in self._cache.postcodes:
|
|
term = self._search_normalized(postcode)
|
|
if not term:
|
|
return
|
|
|
|
with self.conn.cursor() as cur:
|
|
# no word_id needed for postcodes
|
|
cur.execute("""INSERT INTO word (word_token, type, word)
|
|
(SELECT %s, 'P', pc FROM (VALUES (%s)) as v(pc)
|
|
WHERE NOT EXISTS
|
|
(SELECT * FROM word
|
|
WHERE type = 'P' and word = pc))
|
|
""", (term, postcode))
|
|
self._cache.postcodes.add(postcode)
|
|
|
|
|
|
class _TokenInfo:
|
|
""" Collect token information to be sent back to the database.
|
|
"""
|
|
def __init__(self):
|
|
self.names = None
|
|
self.housenumbers = set()
|
|
self.housenumber_tokens = set()
|
|
self.street_tokens = set()
|
|
self.place_tokens = set()
|
|
self.address_tokens = {}
|
|
|
|
|
|
@staticmethod
|
|
def _mk_array(tokens):
|
|
return f"{{{','.join((str(s) for s in tokens))}}}"
|
|
|
|
|
|
def to_dict(self):
|
|
""" Return the token information in database importable format.
|
|
"""
|
|
out = {}
|
|
|
|
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:
|
|
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
|
|
|
|
return out
|
|
|
|
|
|
def set_names(self, fulls, partials):
|
|
""" Adds token information for the normalised names.
|
|
"""
|
|
self.names = self._mk_array(itertools.chain(fulls, partials))
|
|
|
|
|
|
def add_housenumber(self, token, hnr):
|
|
""" Extract housenumber information from a list of normalised
|
|
housenumbers.
|
|
"""
|
|
if token:
|
|
self.housenumbers.add(hnr)
|
|
self.housenumber_tokens.add(token)
|
|
|
|
|
|
def add_street(self, tokens):
|
|
""" Add addr:street match terms.
|
|
"""
|
|
self.street_tokens.update(tokens)
|
|
|
|
|
|
def add_place(self, tokens):
|
|
""" Add addr:place search and match terms.
|
|
"""
|
|
self.place_tokens.update(tokens)
|
|
|
|
|
|
def add_address_term(self, key, partials):
|
|
""" Add additional address terms.
|
|
"""
|
|
if partials:
|
|
self.address_tokens[key] = self._mk_array(partials)
|
|
|
|
|
|
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):
|
|
self.names = {}
|
|
self.partials = {}
|
|
self.fulls = {}
|
|
self.postcodes = set()
|
|
self.housenumbers = {}
|