Nominatim/nominatim/tokenizer/icu_rule_loader.py
Sarah Hoffmann 83054af46f remove typing_extensions requirement
The typing_extensions package is only necessary now when running mypy.
It won't be used at runtime anymore.
2022-07-18 09:55:58 +02:00

184 lines
6.8 KiB
Python

# 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 importlib
import io
import json
import logging
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, Analyser
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, config: Configuration) -> None:
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
rules = get_property(conn, DBCFG_IMPORT_ANALYSIS_RULES)
if rules:
self.analysis_rules = json.loads(rules)
else:
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)
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.
"""
# First apply the normalization rules.
rules = io.StringIO()
rules.write(self.normalization_rules)
# Then add transliteration.
rules.write(self.transliteration_rules)
return rules.getvalue()
def get_normalization_rules(self) -> str:
""" Return rules for normalisation of a term.
"""
return self.normalization_rules
def get_transliteration_rules(self) -> str:
""" Return the rules for converting a string into its asciii representation.
"""
return self.transliteration_rules
def _setup_analysis(self) -> None:
""" Process the rules used for creating the various token analyzers.
"""
self.analysis: Dict[Optional[str], TokenAnalyzerRule] = {}
if not isinstance(self.analysis_rules, list):
raise UsageError("Configuration section 'token-analysis' must be a list.")
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, self.normalization_rules)
@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 = _get_section(rules, section)
if content is None:
return ''
return ';'.join(flatten_config_list(content, section)) + ';'
class TokenAnalyzerRule:
""" Factory for a single analysis module. The class saves the configuration
and creates a new token analyzer on request.
"""
def __init__(self, rules: Mapping[str, Any], normalization_rules: str) -> None:
# Find the analysis module
module_name = 'nominatim.tokenizer.token_analysis.' \
+ _get_section(rules, 'analyzer').replace('-', '_')
self._analysis_mod: AnalysisModule = importlib.import_module(module_name)
# Load the configuration.
self.config = self._analysis_mod.configure(rules, normalization_rules)
def create(self, normalizer: Any, transliterator: Any) -> Analyser:
""" Create a new analyser instance for the given rule.
"""
return self._analysis_mod.create(normalizer, transliterator, self.config)