"""
Helper class to create ICU rules from a configuration file.
"""
-import importlib
+from typing import Mapping, Any, Dict, Optional
import io
import json
import logging
-from nominatim.config import flatten_config_list
+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
-import nominatim.tools.country_info
+from nominatim.tokenizer.token_analysis.base import AnalysisModule, Analyzer
+import nominatim.data.country_info
LOG = logging.getLogger()
DBCFG_IMPORT_ANALYSIS_RULES = "tokenizer_import_analysis_rules"
-def _get_section(rules, section):
+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.
"""
""" Compiler for ICU rules from a tokenizer configuration file.
"""
- def __init__(self, config):
+ 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.tools.country_info.setup_country_config(config)
+ 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.sanitizer_rules = rules.get('sanitizers', [])
- def load_config_from_db(self, conn):
+ def load_config_from_db(self, conn: Connection) -> None:
""" Get previously saved parts of the configuration from the
database.
"""
- self.normalization_rules = get_property(conn, DBCFG_IMPORT_NORM_RULES)
- self.transliteration_rules = get_property(conn, DBCFG_IMPORT_TRANS_RULES)
- self.analysis_rules = json.loads(get_property(conn, DBCFG_IMPORT_ANALYSIS_RULES))
+ 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):
+ 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_ANALYSIS_RULES, json.dumps(self.analysis_rules))
- def make_sanitizer(self):
+ def make_sanitizer(self) -> PlaceSanitizer:
""" Create a place sanitizer from the configured rules.
"""
- return PlaceSanitizer(self.sanitizer_rules)
+ return PlaceSanitizer(self.sanitizer_rules, self.config)
- def make_token_analysis(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):
+ def get_search_rules(self) -> str:
""" Return the ICU rules to be used during search.
The rules combine normalization and transliteration.
"""
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 _setup_analysis(self):
+ def _setup_analysis(self) -> None:
""" Process the rules used for creating the various token analyzers.
"""
- self.analysis = {}
+ self.analysis: Dict[Optional[str], TokenAnalyzerRule] = {}
if not isinstance(self.analysis_rules, list):
raise UsageError("Configuration section 'token-analysis' must be a list.")
+ 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:
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)
+ self.analysis[name] = TokenAnalyzerRule(section, norm, trans,
+ self.config)
@staticmethod
- def _cfg_to_icu_rules(rules, section):
+ 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
and creates a new token analyzer on request.
"""
- def __init__(self, rules, normalization_rules):
- # Find the analysis module
- module_name = 'nominatim.tokenizer.token_analysis.' \
- + _get_section(rules, 'analyzer').replace('-', '_')
- analysis_mod = importlib.import_module(module_name)
- self.create = analysis_mod.create
+ 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")
+
+ self._analysis_mod: AnalysisModule = \
+ config.load_plugin_module(analyzer_name, 'nominatim.tokenizer.token_analysis')
- # Load the configuration.
- self.config = analysis_mod.configure(rules, normalization_rules)
+ self.config = self._analysis_mod.configure(rules, normalizer,
+ transliterator)
+
+
+ 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)