X-Git-Url: https://git.openstreetmap.org./nominatim.git/blobdiff_plain/b894d2c04aed9c8c13e8cae9d8d9e5f0369ad737..fd26310d6adc5fc5685bdd0de36afa66e85b9c9c:/nominatim/tokenizer/icu_tokenizer.py?ds=sidebyside diff --git a/nominatim/tokenizer/icu_tokenizer.py b/nominatim/tokenizer/icu_tokenizer.py index 61263678..799ff559 100644 --- a/nominatim/tokenizer/icu_tokenizer.py +++ b/nominatim/tokenizer/icu_tokenizer.py @@ -1,104 +1,169 @@ +# 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 but using libICU instead of the PostgreSQL module. """ -from collections import Counter +from typing import Optional, Sequence, List, Tuple, Mapping, Any, cast, \ + Dict, Set, Iterable import itertools import json import logging -import re +from pathlib import Path from textwrap import dedent -from nominatim.db.connection import connect -from nominatim.db.properties import set_property, get_property +from nominatim.db.connection import connect, Connection, Cursor +from nominatim.config import Configuration from nominatim.db.utils import CopyBuffer from nominatim.db.sql_preprocessor import SQLPreprocessor +from nominatim.data.place_info import PlaceInfo from nominatim.tokenizer.icu_rule_loader import ICURuleLoader -from nominatim.tokenizer.icu_name_processor import ICUNameProcessor, ICUNameProcessorRules +from nominatim.tokenizer.place_sanitizer import PlaceSanitizer +from nominatim.data.place_name import PlaceName +from nominatim.tokenizer.icu_token_analysis import ICUTokenAnalysis from nominatim.tokenizer.base import AbstractAnalyzer, AbstractTokenizer -DBCFG_MAXWORDFREQ = "tokenizer_maxwordfreq" DBCFG_TERM_NORMALIZATION = "tokenizer_term_normalization" LOG = logging.getLogger() -def create(dsn, data_dir): +def create(dsn: str, data_dir: Path) -> 'ICUTokenizer': """ Create a new instance of the tokenizer provided by this module. """ - return LegacyICUTokenizer(dsn, data_dir) + return ICUTokenizer(dsn, data_dir) -class LegacyICUTokenizer(AbstractTokenizer): - """ This tokenizer uses libICU to covert names and queries to ASCII. +class ICUTokenizer(AbstractTokenizer): + """ This tokenizer uses libICU to convert names and queries to ASCII. Otherwise it uses the same algorithms and data structures as the normalization routines in Nominatim 3. """ - def __init__(self, dsn, data_dir): + def __init__(self, dsn: str, data_dir: Path) -> None: self.dsn = dsn self.data_dir = data_dir - self.naming_rules = None - self.term_normalization = None - self.max_word_frequency = None + self.loader: Optional[ICURuleLoader] = None - def init_new_db(self, config, init_db=True): + 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 sure the tokenizer remains stable even over updates. """ - loader = ICURuleLoader(config.load_sub_configuration('icu_tokenizer.yaml', - config='TOKENIZER_CONFIG')) - self.naming_rules = ICUNameProcessorRules(loader=loader) - self.term_normalization = config.TERM_NORMALIZATION - self.max_word_frequency = config.MAX_WORD_FREQUENCY + self.loader = ICURuleLoader(config) - self._install_php(config.lib_dir.php) - self._save_config(config) + self._install_php(config.lib_dir.php, overwrite=True) + self._save_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. """ + self.loader = ICURuleLoader(config) + with connect(self.dsn) as conn: - self.naming_rules = ICUNameProcessorRules(conn=conn) - self.term_normalization = get_property(conn, DBCFG_TERM_NORMALIZATION) - self.max_word_frequency = get_property(conn, DBCFG_MAXWORDFREQ) + self.loader.load_config_from_db(conn) + + self._install_php(config.lib_dir.php, overwrite=False) - def finalize_import(self, _): + 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: - max_word_freq = get_property(conn, DBCFG_MAXWORDFREQ) sqlp = SQLPreprocessor(conn, config) - sqlp.run_sql_file(conn, 'tokenizer/icu_tokenizer.sql', - max_word_freq=max_word_freq) + sqlp.run_sql_file(conn, 'tokenizer/icu_tokenizer.sql') - def check_database(self): + def check_database(self, config: Configuration) -> None: """ Check that the tokenizer is set up correctly. """ - self.init_from_project() + # Will throw an error if there is an issue. + self.init_from_project(config) + + + def update_statistics(self) -> None: + """ Recompute frequencies for all name 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 info = info || jsonb_build_object('count', count) + FROM word_frequencies WHERE word_id = id""") + cur.drop_table("word_frequencies") + conn.commit() + - if self.naming_rules is None: - return "Configuration for tokenizer 'icu' are missing." + def _cleanup_housenumbers(self) -> None: + """ Remove unused house numbers. + """ + with connect(self.dsn) as conn: + if not conn.table_exists('search_name'): + return + with conn.cursor(name="hnr_counter") as cur: + cur.execute("""SELECT DISTINCT word_id, coalesce(info->>'lookup', word_token) + FROM word + WHERE type = 'H' + AND NOT EXISTS(SELECT * FROM search_name + WHERE ARRAY[word.word_id] && name_vector) + AND (char_length(coalesce(word, word_token)) > 6 + OR coalesce(word, word_token) not similar to '\\d+') + """) + candidates = {token: wid for wid, token in cur} + with conn.cursor(name="hnr_counter") as cur: + cur.execute("""SELECT housenumber FROM placex + WHERE housenumber is not null + AND (char_length(housenumber) > 6 + OR housenumber not similar to '\\d+') + """) + for row in cur: + for hnr in row[0].split(';'): + candidates.pop(hnr, None) + LOG.info("There are %s outdated housenumbers.", len(candidates)) + LOG.debug("Outdated housenumbers: %s", candidates.keys()) + if candidates: + with conn.cursor() as cur: + cur.execute("""DELETE FROM word WHERE word_id = any(%s)""", + (list(candidates.values()), )) + conn.commit() - return None - def name_analyzer(self): + def update_word_tokens(self) -> None: + """ Remove unused tokens. + """ + LOG.warning("Cleaning up housenumber tokens.") + self._cleanup_housenumbers() + LOG.warning("Tokenizer house-keeping done.") + + + def name_analyzer(self) -> 'ICUNameAnalyzer': """ Create a new analyzer for tokenizing names and queries using this tokinzer. Analyzers are context managers and should be used accordingly: @@ -113,33 +178,48 @@ class LegacyICUTokenizer(AbstractTokenizer): Analyzers are not thread-safe. You need to instantiate one per thread. """ - return LegacyICUNameAnalyzer(self.dsn, ICUNameProcessor(self.naming_rules)) + assert self.loader is not None + return ICUNameAnalyzer(self.dsn, self.loader.make_sanitizer(), + self.loader.make_token_analysis()) - def _install_php(self, phpdir): + def most_frequent_words(self, conn: Connection, num: int) -> List[str]: + """ Return a list of the `num` most frequent full words + in the database. + """ + with conn.cursor() as cur: + cur.execute("""SELECT word, sum((info->>'count')::int) as count + FROM word WHERE type = 'W' + GROUP BY word + ORDER BY count DESC LIMIT %s""", (num,)) + return list(s[0].split('@')[0] for s in cur) + + + def _install_php(self, phpdir: Path, overwrite: bool = True) -> None: """ Install the php script for the tokenizer. """ + assert self.loader is not None php_file = self.data_dir / "tokenizer.php" - php_file.write_text(dedent(f"""\ - None: """ Save the configuration that needs to remain stable for the given database as database properties. """ + assert self.loader is not None with connect(self.dsn) as conn: - self.naming_rules.save_rules(conn) + self.loader.save_config_to_db(conn) - set_property(conn, DBCFG_MAXWORDFREQ, config.MAX_WORD_FREQUENCY) - set_property(conn, DBCFG_TERM_NORMALIZATION, self.term_normalization) - - 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. """ @@ -148,62 +228,25 @@ class LegacyICUTokenizer(AbstractTokenizer): sqlp.run_sql_file(conn, 'tokenizer/icu_tokenizer_tables.sql') conn.commit() - LOG.warning("Precomputing word tokens") - - # get partial words and their frequencies - words = self._count_partial_terms(conn) - - # copy them back into the word table - with CopyBuffer() as copystr: - for term, cnt in words.items(): - copystr.add('w', term, json.dumps({'count': cnt})) - - with conn.cursor() as cur: - copystr.copy_out(cur, 'word', - columns=['type', 'word_token', 'info']) - cur.execute("""UPDATE word SET word_id = nextval('seq_word') - WHERE word_id is null and type = 'w'""") - - conn.commit() - - def _count_partial_terms(self, conn): - """ Count the partial terms from the names in the place table. - """ - words = Counter() - name_proc = ICUNameProcessor(self.naming_rules) - - with conn.cursor(name="words") as cur: - cur.execute(""" SELECT v, count(*) FROM - (SELECT svals(name) as v FROM place)x - WHERE length(v) < 75 GROUP BY v""") - - for name, cnt in cur: - terms = set() - for word in name_proc.get_variants_ascii(name_proc.get_normalized(name)): - if ' ' in word: - terms.update(word.split()) - for term in terms: - words[term] += cnt - - return words - -class LegacyICUNameAnalyzer(AbstractAnalyzer): - """ The legacy analyzer uses the ICU library for splitting names. +class ICUNameAnalyzer(AbstractAnalyzer): + """ The ICU analyzer uses the ICU library for splitting names. Each instance opens a connection to the database to request the normalization. """ - def __init__(self, dsn, name_proc): - self.conn = connect(dsn).connection + def __init__(self, dsn: str, sanitizer: PlaceSanitizer, + token_analysis: ICUTokenAnalysis) -> None: + self.conn: Optional[Connection] = connect(dsn).connection self.conn.autocommit = True - self.name_processor = name_proc + self.sanitizer = sanitizer + self.token_analysis = token_analysis self._cache = _TokenCache() - def close(self): + def close(self) -> None: """ Free all resources used by the analyzer. """ if self.conn: @@ -211,7 +254,20 @@ class LegacyICUNameAnalyzer(AbstractAnalyzer): self.conn = None - def get_word_token_info(self, words): + def _search_normalized(self, name: str) -> str: + """ Return the search token transliteration of the given name. + """ + return cast(str, self.token_analysis.search.transliterate(name)).strip() + + + def _normalized(self, name: str) -> str: + """ Return the normalized version of the given name with all + non-relevant information removed. + """ + return cast(str, self.token_analysis.normalizer.transliterate(name)).strip() + + + 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. @@ -222,13 +278,14 @@ class LegacyICUNameAnalyzer(AbstractAnalyzer): The function is used for testing and debugging only and not necessarily efficient. """ + assert self.conn is not None full_tokens = {} partial_tokens = {} for word in words: if word.startswith('#'): - full_tokens[word] = self.name_processor.get_search_normalized(word[1:]) + full_tokens[word] = self._search_normalized(word[1:]) else: - partial_tokens[word] = self.name_processor.get_search_normalized(word) + partial_tokens[word] = self._search_normalized(word) with self.conn.cursor() as cur: cur.execute("""SELECT word_token, word_id @@ -244,8 +301,7 @@ class LegacyICUNameAnalyzer(AbstractAnalyzer): + [(k, v, part_ids.get(v, None)) for k, v in partial_tokens.items()] - @staticmethod - def normalize_postcode(postcode): + 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 @@ -254,53 +310,92 @@ class LegacyICUNameAnalyzer(AbstractAnalyzer): return postcode.strip().upper() - def _make_standard_hnr(self, hnr): - """ Create a normalised version of a housenumber. - - This function takes minor shortcuts on transliteration. - """ - return self.name_processor.get_search_normalized(hnr) - - def update_postcodes_from_db(self): + def update_postcodes_from_db(self) -> None: """ Update postcode tokens in the word table from the location_postcode table. """ - to_delete = [] + assert self.conn is not None + analyzer = self.token_analysis.analysis.get('@postcode') + 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 type = 'P') w - ON pc = word) x - WHERE pc is null or word is null""") - - with CopyBuffer() as copystr: - for postcode, word in cur: - if postcode is None: - to_delete.append(word) - else: - copystr.add(self.name_processor.get_search_normalized(postcode), - 'P', postcode) - - if to_delete: - cur.execute("""DELETE FROM WORD - WHERE type ='P' and word = any(%s) - """, (to_delete, )) - - copystr.copy_out(cur, 'word', - columns=['word_token', 'type', 'word']) - - - def update_special_phrases(self, phrases, should_replace): + # First get all postcode names currently in the word table. + cur.execute("SELECT DISTINCT word FROM word WHERE type = 'P'") + word_entries = set((entry[0] for entry in cur)) + + # Then compute the required postcode names from the postcode table. + needed_entries = set() + cur.execute("SELECT country_code, postcode FROM location_postcode") + for cc, postcode in cur: + info = PlaceInfo({'country_code': cc, + 'class': 'place', 'type': 'postcode', + 'address': {'postcode': postcode}}) + address = self.sanitizer.process_names(info)[1] + for place in address: + if place.kind == 'postcode': + if analyzer is None: + postcode_name = place.name.strip().upper() + variant_base = None + else: + postcode_name = analyzer.get_canonical_id(place) + variant_base = place.get_attr("variant") + + if variant_base: + needed_entries.add(f'{postcode_name}@{variant_base}') + else: + needed_entries.add(postcode_name) + break + + # Now update the word table. + self._delete_unused_postcode_words(word_entries - needed_entries) + self._add_missing_postcode_words(needed_entries - word_entries) + + def _delete_unused_postcode_words(self, tokens: Iterable[str]) -> None: + assert self.conn is not None + if tokens: + with self.conn.cursor() as cur: + cur.execute("DELETE FROM word WHERE type = 'P' and word = any(%s)", + (list(tokens), )) + + def _add_missing_postcode_words(self, tokens: Iterable[str]) -> None: + assert self.conn is not None + if not tokens: + return + + analyzer = self.token_analysis.analysis.get('@postcode') + terms = [] + + for postcode_name in tokens: + if '@' in postcode_name: + term, variant = postcode_name.split('@', 2) + term = self._search_normalized(term) + if analyzer is None: + variants = [term] + else: + variants = analyzer.compute_variants(variant) + if term not in variants: + variants.append(term) + else: + variants = [self._search_normalized(postcode_name)] + terms.append((postcode_name, variants)) + + if terms: + with self.conn.cursor() as cur: + cur.execute_values("""SELECT create_postcode_word(pc, var) + FROM (VALUES %s) AS v(pc, var)""", + terms) + + + + + 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. If `should_replace` is True, then the previous set of will be completely replaced. Otherwise the phrases are added to the already existing ones. """ - norm_phrases = set(((self.name_processor.get_normalized(p[0]), p[1], p[2], p[3]) + assert self.conn is not None + norm_phrases = set(((self._normalized(p[0]), p[1], p[2], p[3]) for p in phrases)) with self.conn.cursor() as cur: @@ -322,7 +417,9 @@ class LegacyICUNameAnalyzer(AbstractAnalyzer): len(norm_phrases), added, deleted) - def _add_special_phrases(self, cursor, new_phrases, existing_phrases): + def _add_special_phrases(self, cursor: Cursor, + new_phrases: Set[Tuple[str, str, str, str]], + existing_phrases: Set[Tuple[str, str, str, str]]) -> int: """ Add all phrases to the database that are not yet there. """ to_add = new_phrases - existing_phrases @@ -330,7 +427,7 @@ class LegacyICUNameAnalyzer(AbstractAnalyzer): added = 0 with CopyBuffer() as copystr: for word, cls, typ, oper in to_add: - term = self.name_processor.get_search_normalized(word) + term = self._search_normalized(word) if term: copystr.add(term, 'S', word, json.dumps({'class': cls, 'type': typ, @@ -343,9 +440,10 @@ class LegacyICUNameAnalyzer(AbstractAnalyzer): return added - @staticmethod - def _remove_special_phrases(cursor, new_phrases, existing_phrases): - """ Remove all phrases from the databse that are no longer in the + def _remove_special_phrases(self, cursor: Cursor, + new_phrases: Set[Tuple[str, str, str, str]], + existing_phrases: Set[Tuple[str, str, str, str]]) -> int: + """ Remove all phrases from the database that are no longer in the new phrase list. """ to_delete = existing_phrases - new_phrases @@ -361,106 +459,230 @@ class LegacyICUNameAnalyzer(AbstractAnalyzer): return len(to_delete) - def add_country_names(self, country_code, names): - """ Add names for the given country to the search index. + def add_country_names(self, country_code: str, names: Mapping[str, str]) -> None: + """ Add default names for the given country to the search index. """ + # Make sure any name preprocessing for country names applies. + info = PlaceInfo({'name': names, 'country_code': country_code, + 'rank_address': 4, 'class': 'boundary', + 'type': 'administrative'}) + self._add_country_full_names(country_code, + self.sanitizer.process_names(info)[0], + internal=True) + + + def _add_country_full_names(self, country_code: str, names: Sequence[PlaceName], + internal: bool = False) -> None: + """ Add names for the given country from an already sanitized + name list. + """ + assert self.conn is not None word_tokens = set() - for name in self._compute_full_names(names): - norm_name = self.name_processor.get_search_normalized(name) + for name in names: + norm_name = self._search_normalized(name.name) if norm_name: word_tokens.add(norm_name) with self.conn.cursor() as cur: # Get existing names - cur.execute("""SELECT word_token FROM word - WHERE type = 'C' and word = %s""", + cur.execute("""SELECT word_token, coalesce(info ? 'internal', false) as is_internal + FROM word + WHERE type = 'C' and word = %s""", (country_code, )) - word_tokens.difference_update((t[0] for t in cur)) + # 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) 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. - if word_tokens: - cur.execute("""INSERT INTO word (word_token, type, word) - (SELECT token, 'C', %s - FROM unnest(%s) as token) - """, (country_code, list(word_tokens))) - - # No names are deleted at the moment. - # If deletion is made possible, then the static names from the - # initial 'country_name' table should be kept. - - - def process_place(self, place): + 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) as token) + """ + else: + sql = """INSERT INTO word (word_token, type, word) + (SELECT token, 'C', %s + FROM unnest(%s) 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-serialisable structure that will be handed into + Returns a JSON-serializable structure that will be handed into the database via the token_info field. """ - token_info = _TokenInfo(self._cache) + token_info = _TokenInfo() - names = place.get('name') + names, address = self.sanitizer.process_names(place) if names: - fulls, partials = self._compute_name_tokens(names) - - token_info.add_names(fulls, partials) + token_info.set_names(*self._compute_name_tokens(names)) - country_feature = place.get('country_feature') - if country_feature and re.fullmatch(r'[A-Za-z][A-Za-z]', country_feature): - self.add_country_names(country_feature.lower(), names) + if place.is_country(): + assert place.country_code is not None + self._add_country_full_names(place.country_code, names) - address = place.get('address') if address: self._process_place_address(token_info, address) - return token_info.data + 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(self._compute_partial_tokens(item.name)) + elif not item.kind.startswith('_') and not item.suffix and \ + item.kind not in ('country', 'full', 'inclusion'): + token_info.add_address_term(item.kind, self._compute_partial_tokens(item.name)) + + + 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: + with self.conn.cursor() as cur: + hid = cur.scalar("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: + variants = analyzer.compute_variants(word_id) + if variants: + with self.conn.cursor() as cur: + hid = cur.scalar("SELECT create_analyzed_hnr_id(%s, %s)", + (word_id, list(variants))) + result = hid, variants[0] + self._cache.housenumbers[word_id] = result + + return result + + + def _compute_partial_tokens(self, name: str) -> List[int]: + """ Normalize the given term, split it into partial words and return + then token list for them. + """ + assert self.conn is not None + 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, )) - def _process_place_address(self, token_info, address): - hnrs = [] - addr_terms = [] - for key, value in address.items(): - if key == 'postcode': - self._add_postcode(value) - elif key in ('housenumber', 'streetnumber', 'conscriptionnumber'): - hnrs.append(value) - elif key == 'street': - token_info.add_street(*self._compute_name_tokens({'name': value})) - elif key == 'place': - token_info.add_place(*self._compute_name_tokens({'name': value})) - elif not key.startswith('_') and \ - key not in ('country', 'full'): - addr_terms.append((key, *self._compute_name_tokens({'name': value}))) + for partial, token in cur: + assert token is not None + tokens.append(token) + self._cache.partials[partial] = token - if hnrs: - hnrs = self._split_housenumbers(hnrs) - token_info.add_housenumbers(self.conn, [self._make_standard_hnr(n) for n in hnrs]) + return tokens - if addr_terms: - token_info.add_address_terms(addr_terms) + 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] - def _compute_name_tokens(self, names): + 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. """ - full_names = self._compute_full_names(names) - full_tokens = set() - partial_tokens = set() + 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}' - for name in full_names: - norm_name = self.name_processor.get_normalized(name) - full, part = self._cache.names.get(norm_name, (None, None)) + full, part = self._cache.names.get(token_id, (None, None)) if full is None: - variants = self.name_processor.get_variants_ascii(norm_name) + variants = analyzer.compute_variants(word_id) if not variants: continue with self.conn.cursor() as cur: - cur.execute("SELECT (getorcreate_full_word(%s, %s)).*", - (norm_name, variants)) - full, part = cur.fetchone() + cur.execute("SELECT * FROM getorcreate_full_word(%s, %s)", + (token_id, variants)) + full, part = cast(Tuple[int, List[int]], cur.fetchone()) + + self._cache.names[token_id] = (full, part) - self._cache.names[norm_name] = (full, part) + assert part is not None full_tokens.add(full) partial_tokens.update(part) @@ -468,116 +690,125 @@ class LegacyICUNameAnalyzer(AbstractAnalyzer): return full_tokens, partial_tokens - @staticmethod - def _compute_full_names(names): - """ Return the set of all full name word ids to be used with the - given dictionary of names. - """ - full_names = set() - for name in (n.strip() for ns in names.values() for n in re.split('[;,]', ns)): - if name: - full_names.add(name) - - brace_idx = name.find('(') - if brace_idx >= 0: - full_names.add(name[:brace_idx].strip()) - - return full_names - - - def _add_postcode(self, postcode): + def _add_postcode(self, item: PlaceName) -> Optional[str]: """ Make sure the normalized postcode is present in the word table. """ - if re.search(r'[:,;]', postcode) is None: - postcode = self.normalize_postcode(postcode) + assert self.conn is not None + analyzer = self.token_analysis.analysis.get('@postcode') - if postcode not in self._cache.postcodes: - term = self.name_processor.get_search_normalized(postcode) - if not term: - return + if analyzer is None: + postcode_name = item.name.strip().upper() + variant_base = None + else: + postcode_name = analyzer.get_canonical_id(item) + variant_base = item.get_attr("variant") - 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) - - - @staticmethod - def _split_housenumbers(hnrs): - if len(hnrs) > 1 or ',' in hnrs[0] or ';' in hnrs[0]: - # split numbers if necessary - simple_list = [] - for hnr in hnrs: - simple_list.extend((x.strip() for x in re.split(r'[;,]', hnr))) - - if len(simple_list) > 1: - hnrs = list(set(simple_list)) - else: - hnrs = simple_list + if variant_base: + postcode = f'{postcode_name}@{variant_base}' + else: + postcode = postcode_name - return hnrs + if postcode not in self._cache.postcodes: + term = self._search_normalized(postcode_name) + if not term: + return None + variants = {term} + if analyzer is not None and variant_base: + variants.update(analyzer.compute_variants(variant_base)) + with self.conn.cursor() as cur: + cur.execute("SELECT create_postcode_word(%s, %s)", + (postcode, list(variants))) + self._cache.postcodes.add(postcode) + + return postcode_name class _TokenInfo: """ Collect token information to be sent back to the database. """ - def __init__(self, cache): - self._cache = cache - self.data = {} + 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 - @staticmethod - def _mk_array(tokens): - return '{%s}' % ','.join((str(s) for s in tokens)) + 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) - def add_names(self, fulls, partials): + 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.data['names'] = self._mk_array(itertools.chain(fulls, partials)) + self.names = self._mk_array(itertools.chain(fulls, partials)) - def add_housenumbers(self, conn, hnrs): + def add_housenumber(self, token: Optional[int], hnr: Optional[str]) -> None: """ Extract housenumber information from a list of normalised housenumbers. """ - self.data['hnr_tokens'] = self._mk_array(self._cache.get_hnr_tokens(conn, hnrs)) - self.data['hnr'] = ';'.join(hnrs) + if token: + assert hnr is not None + self.housenumbers.add(hnr) + self.housenumber_tokens.add(token) - def add_street(self, fulls, _): + def add_street(self, tokens: Iterable[int]) -> None: """ Add addr:street match terms. """ - if fulls: - self.data['street'] = self._mk_array(fulls) + if self.street_tokens is None: + self.street_tokens = set() + self.street_tokens.update(tokens) - def add_place(self, fulls, partials): + def add_place(self, tokens: Iterable[int]) -> None: """ Add addr:place search and match terms. """ - if fulls: - self.data['place_search'] = self._mk_array(itertools.chain(fulls, partials)) - self.data['place_match'] = self._mk_array(fulls) + self.place_tokens.update(tokens) - def add_address_terms(self, terms): + def add_address_term(self, key: str, partials: Iterable[int]) -> None: """ Add additional address terms. """ - tokens = {} - - for key, fulls, partials in terms: - if fulls: - tokens[key] = [self._mk_array(itertools.chain(fulls, partials)), - self._mk_array(fulls)] + if partials: + self.address_tokens[key] = self._mk_array(partials) - if tokens: - self.data['addr'] = tokens + def set_postcode(self, postcode: Optional[str]) -> None: + """ Set the postcode to the given one. + """ + self.postcode = postcode class _TokenCache: @@ -586,33 +817,9 @@ class _TokenCache: This cache is not thread-safe and needs to be instantiated per analyzer. """ - def __init__(self): - self.names = {} - self.postcodes = set() - self.housenumbers = {} - - - def get_hnr_tokens(self, conn, terms): - """ Get token ids for a list of housenumbers, looking them up in the - database if necessary. `terms` is an iterable of normalized - housenumbers. - """ - tokens = [] - askdb = [] - - for term in terms: - token = self.housenumbers.get(term) - if token is None: - askdb.append(term) - else: - tokens.append(token) - - if askdb: - with conn.cursor() as cur: - cur.execute("SELECT nr, getorcreate_hnr_id(nr) FROM unnest(%s) as nr", - (askdb, )) - for term, tid in cur: - self.housenumbers[term] = tid - tokens.append(tid) - - return tokens + def __init__(self) -> None: + self.names: Dict[str, Tuple[int, List[int]]] = {} + self.partials: Dict[str, int] = {} + self.fulls: Dict[str, List[int]] = {} + self.postcodes: Set[str] = set() + self.housenumbers: Dict[str, Tuple[Optional[int], Optional[str]]] = {}