X-Git-Url: https://git.openstreetmap.org./nominatim.git/blobdiff_plain/f70930b1a04629a33241047586bda54bc0176dc7..7b0e0dfd883b268b58a721e2967303fa368e563f:/nominatim/tokenizer/icu_rule_loader.py diff --git a/nominatim/tokenizer/icu_rule_loader.py b/nominatim/tokenizer/icu_rule_loader.py index 6bf23201..4c36282c 100644 --- a/nominatim/tokenizer/icu_rule_loader.py +++ b/nominatim/tokenizer/icu_rule_loader.py @@ -1,35 +1,110 @@ +# 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. """ Helper class to create ICU rules from a configuration file. """ +from typing import Mapping, Any, Dict, Optional import io +import json import logging -from collections import defaultdict -import itertools -import yaml from icu import Transliterator +from nominatim.config import flatten_config_list, Configuration +from nominatim.db.properties import set_property, get_property +from nominatim.db.connection import Connection from nominatim.errors import UsageError +from nominatim.tokenizer.place_sanitizer import PlaceSanitizer +from nominatim.tokenizer.icu_token_analysis import ICUTokenAnalysis +from nominatim.tokenizer.token_analysis.base import AnalysisModule, Analyzer +import nominatim.data.country_info LOG = logging.getLogger() +DBCFG_IMPORT_NORM_RULES = "tokenizer_import_normalisation" +DBCFG_IMPORT_TRANS_RULES = "tokenizer_import_transliteration" +DBCFG_IMPORT_ANALYSIS_RULES = "tokenizer_import_analysis_rules" + + +def _get_section(rules: Mapping[str, Any], section: str) -> Any: + """ Get the section named 'section' from the rules. If the section does + not exist, raise a usage error with a meaningful message. + """ + if section not in rules: + LOG.fatal("Section '%s' not found in tokenizer config.", section) + raise UsageError("Syntax error in tokenizer configuration file.") + + return rules[section] + class ICURuleLoader: """ Compiler for ICU rules from a tokenizer configuration file. """ - def __init__(self, configfile): - self.configfile = configfile - self.compound_suffixes = set() - self.abbreviations = defaultdict() + def __init__(self, config: Configuration) -> None: + self.config = config + rules = config.load_sub_configuration('icu_tokenizer.yaml', + config='TOKENIZER_CONFIG') + + # Make sure country information is available to analyzers and sanitizers. + nominatim.data.country_info.setup_country_config(config) + + self.normalization_rules = self._cfg_to_icu_rules(rules, 'normalization') + self.transliteration_rules = self._cfg_to_icu_rules(rules, 'transliteration') + self.analysis_rules = _get_section(rules, 'token-analysis') + self._setup_analysis() + + # Load optional sanitizer rule set. + self.sanitizer_rules = rules.get('sanitizers', []) + + + def load_config_from_db(self, conn: Connection) -> None: + """ Get previously saved parts of the configuration from the + database. + """ + rules = get_property(conn, DBCFG_IMPORT_NORM_RULES) + if rules is not None: + self.normalization_rules = rules + + rules = get_property(conn, DBCFG_IMPORT_TRANS_RULES) + if rules is not None: + self.transliteration_rules = rules - if configfile.suffix == '.yaml': - self._load_from_yaml() + rules = get_property(conn, DBCFG_IMPORT_ANALYSIS_RULES) + if rules: + self.analysis_rules = json.loads(rules) else: - raise UsageError("Unknown format of tokenizer configuration.") + self.analysis_rules = [] + self._setup_analysis() + + + def save_config_to_db(self, conn: Connection) -> None: + """ Save the part of the configuration that cannot be changed into + the database. + """ + set_property(conn, DBCFG_IMPORT_NORM_RULES, self.normalization_rules) + set_property(conn, DBCFG_IMPORT_TRANS_RULES, self.transliteration_rules) + set_property(conn, DBCFG_IMPORT_ANALYSIS_RULES, json.dumps(self.analysis_rules)) + + + def make_sanitizer(self) -> PlaceSanitizer: + """ Create a place sanitizer from the configured rules. + """ + return PlaceSanitizer(self.sanitizer_rules, self.config) - def get_search_rules(self): + def make_token_analysis(self) -> ICUTokenAnalysis: + """ Create a token analyser from the reviouly loaded rules. + """ + return ICUTokenAnalysis(self.normalization_rules, + self.transliteration_rules, self.analysis) + + + def get_search_rules(self) -> str: """ Return the ICU rules to be used during search. The rules combine normalization and transliteration. """ @@ -41,123 +116,81 @@ class ICURuleLoader: rules.write(self.transliteration_rules) return rules.getvalue() - def get_normalization_rules(self): + + def get_normalization_rules(self) -> str: """ Return rules for normalisation of a term. """ return self.normalization_rules - def get_transliteration_rules(self): + + def get_transliteration_rules(self) -> str: """ Return the rules for converting a string into its asciii representation. """ return self.transliteration_rules - def get_replacement_pairs(self): - """ Return the list of possible compound decompositions with - application of abbreviations included. - The result is a list of pairs: the first item is the sequence to - replace, the second is a list of replacements. - """ - synonyms = defaultdict(set) - - # First add entries for compound decomposition. - for suffix in self.compound_suffixes: - variants = (suffix + ' ', ' ' + suffix + ' ') - for key in variants: - synonyms[key].update(variants) - - for full, abbr in self.abbreviations.items(): - key = ' ' + full + ' ' - # Entries in the abbreviation list always apply to full words: - synonyms[key].update((' ' + a + ' ' for a in abbr)) - # Replacements are optional, so add a noop - synonyms[key].add(key) - - if full in self.compound_suffixes: - # Full word abbreviating to compunded version. - synonyms[key].update((a + ' ' for a in abbr)) - - key = full + ' ' - # Uncompunded suffix abbrevitating to decompounded version. - synonyms[key].update((' ' + a + ' ' for a in abbr)) - # Uncompunded suffix abbrevitating to compunded version. - synonyms[key].update((a + ' ' for a in abbr)) - - # sort the resulting list by descending length (longer matches are prefered). - sorted_keys = sorted(synonyms.keys(), key=len, reverse=True) - - return [(k, list(synonyms[k])) for k in sorted_keys] - - def _load_from_yaml(self): - rules = yaml.safe_load(self.configfile.read_text()) - - self.normalization_rules = self._cfg_to_icu_rules(rules, 'normalization') - self.transliteration_rules = self._cfg_to_icu_rules(rules, 'transliteration') - self._parse_compound_suffix_list(self._get_section(rules, 'compound_suffixes')) - self._parse_abbreviation_list(self._get_section(rules, 'abbreviations')) - - - def _get_section(self, rules, section): - """ Get the section named 'section' from the rules. If the section does - not exist, raise a usage error with a meaningful message. + def _setup_analysis(self) -> None: + """ Process the rules used for creating the various token analyzers. """ - if section not in rules: - LOG.fatal("Section '%s' not found in tokenizer config '%s'.", - section, str(self.configfile)) - raise UsageError("Syntax error in tokenizer configuration file.") - - return rules[section] + self.analysis: Dict[Optional[str], TokenAnalyzerRule] = {} + if not isinstance(self.analysis_rules, list): + raise UsageError("Configuration section 'token-analysis' must be a list.") - def _cfg_to_icu_rules(self, rules, section): + norm = Transliterator.createFromRules("rule_loader_normalization", + self.normalization_rules) + trans = Transliterator.createFromRules("rule_loader_transliteration", + self.transliteration_rules) + + for section in self.analysis_rules: + name = section.get('id', None) + if name in self.analysis: + if name is None: + LOG.fatal("ICU tokenizer configuration has two default token analyzers.") + else: + LOG.fatal("ICU tokenizer configuration has two token " + "analyzers with id '%s'.", name) + raise UsageError("Syntax error in ICU tokenizer config.") + self.analysis[name] = TokenAnalyzerRule(section, norm, trans, + self.config) + + + @staticmethod + def _cfg_to_icu_rules(rules: Mapping[str, Any], section: str) -> str: """ Load an ICU ruleset from the given section. If the section is a simple string, it is interpreted as a file name and the rules are loaded verbatim from the given file. The filename is expected to be relative to the tokenizer rule file. If the section is a list then each line is assumed to be a rule. All rules are concatenated and returned. """ - content = self._get_section(rules, section) + content = _get_section(rules, section) if content is None: return '' - if isinstance(content, str): - return (self.configfile.parent / content).read_text().replace('\n', ' ') - - return ';'.join(content) + ';' - + return ';'.join(flatten_config_list(content, section)) + ';' - def _parse_compound_suffix_list(self, rules): - if not rules: - self.compound_suffixes = set() - return - - norm = Transliterator.createFromRules("rule_loader_normalization", - self.normalization_rules) - # Make sure all suffixes are in their normalised form. - self.compound_suffixes = set((norm.transliterate(s) for s in rules)) - - - def _parse_abbreviation_list(self, rules): - self.abbreviations = defaultdict(list) +class TokenAnalyzerRule: + """ Factory for a single analysis module. The class saves the configuration + and creates a new token analyzer on request. + """ - if not rules: - return + def __init__(self, rules: Mapping[str, Any], + normalizer: Any, transliterator: Any, + config: Configuration) -> None: + analyzer_name = _get_section(rules, 'analyzer') + if not analyzer_name or not isinstance(analyzer_name, str): + raise UsageError("'analyzer' parameter needs to be simple string") - norm = Transliterator.createFromRules("rule_loader_normalization", - self.normalization_rules) + self._analysis_mod: AnalysisModule = \ + config.load_plugin_module(analyzer_name, 'nominatim.tokenizer.token_analysis') - for rule in rules: - parts = rule.split('=>') - if len(parts) != 2: - LOG.fatal("Syntax error in abbreviation section, line: %s", rule) - raise UsageError("Syntax error in tokenizer configuration file.") + self.config = self._analysis_mod.configure(rules, normalizer, + transliterator) - # Make sure all terms match the normalised version. - fullterms = (norm.transliterate(t.strip()) for t in parts[0].split(',')) - abbrterms = (norm.transliterate(t.strip()) for t in parts[1].split(',')) - for full, abbr in itertools.product(fullterms, abbrterms): - if full and abbr: - self.abbreviations[full].append(abbr) + def create(self, normalizer: Any, transliterator: Any) -> Analyzer: + """ Create a new analyser instance for the given rule. + """ + return self._analysis_mod.create(normalizer, transliterator, self.config)